• TABLE OF CONTENTS
HIDE
 Front Cover
 Title Page
 Table of Contents
 Preface
 Foreword
 Acknowledgement
 Introduction
 Planning applied research
 Conducting applied research
 Reference
 An applied research project...
 Back Cover






Title: Planning and conducting applied research
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Permanent Link: http://ufdc.ufl.edu/UF00055253/00001
 Material Information
Title: Planning and conducting applied research
Physical Description: x, 116 p. : ill. ; 26 cm.
Language: English
Creator: Andrew, Chris O
Hildebrand, Peter E. ( joint author )
Publisher: MSS Information Corp.
Place of Publication: New York
Publication Date: c1976
 Subjects
Subject: Research -- Methodology   ( lcsh )
Genre: bibliography   ( marcgt )
non-fiction   ( marcgt )
 Notes
Bibliography: Bibliography: p. 100-106.
Statement of Responsibility: by Chris O. Andrew, Peter E. Hildebrand.
Funding: Electronic resources created as part of a prototype UF Institutional Repository and Faculty Papers project by the University of Florida.
 Record Information
Bibliographic ID: UF00055253
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: aleph - 000147489
oclc - 01991214
notis - AAR3712
lccn - 75045131
isbn - 0842205349

Table of Contents
    Front Cover
        Front Cover
    Title Page
        Title Page 1
        Title Page 2
    Table of Contents
        Page i
        Page ii
        Page iii
        Page iv
    Preface
        Page v
        Page vi
    Foreword
        Page vii
        Page viii
    Acknowledgement
        Page ix
        Page x
    Introduction
        Page 1
        Page 2
        Applied research
            Page 3
            Page 4
        The book
            Page 5
            Page 6
            Page 7
    Planning applied research
        Page 8
        Effects of resource availability on applied research
            Page 9
            Page 10
            Information resources
                Page 11
                Secondary and primary information
                    Page 12
                Time series and cross-section data
                    Page 13
                Experimental and non-experimental data
                    Page 14
            Human resources
                Page 15
            Physical resources
                Page 16
            Financial resources
                Page 17
            Time constraints
                Page 17
            Summary
                Page 18
        Orientation and focus of projects: Researchable problems, hypotheses, and objectives
            Page 19
            A conceptual model
                Page 19
                Page 20
                Page 21
            Specification of a researchable problem
                Page 22
                Problems reflect felt needs
                    Page 23
                Problems are non-hypothetical
                    Page 24
                Problemns suggest meaningful, testable hypothesis
                    Page 25
                Problems are relevant and manageable
                    Page 25
                Researchable problems vs. problematic situations
                    Page 26
                Examples of problem statements
                    Page 27
                    Page 28
                    Page 29
                    Page 30
            Formulation of the hypotheses
                Page 31
                Characteristics of hypotheses
                    Page 32
                Some examples of hypotheses
                    Page 33
                    Page 34
                    Page 35
                    Page 36
                    Page 37
            Delineation of the objectives
                Page 38
                Page 39
                Page 40
            Summary
                Page 41
                Page 42
                Page 43
                Page 44
    Conducting applied research
        Page 45
        Experimental data collection
            Page 46
            Experimental design
                Page 47
                Relationship to the problem
                    Page 48
                    Page 49
                    Page 50
                    Page 51
                Relationship to resources
                    Page 52
                    Page 53
                    Page 54
                    Page 55
            Secondary experimental data
                Page 56
                Page 57
            Multi-purpose experimentation
                Page 58
                Page 59
                Page 60
                Page 61
            Summary
                Page 62
                Page 63
        Non-experimental data collection
            Page 64
            Selecting respondents
                Page 65
                Page 66
            Designing the questionnaire
                Page 67
                Difficulties in interpretation and communication
                    Page 68
                    Page 69
                Designing for data retrieval
                    Page 70
                    Page 71
            Pretesting the questionnaire
                Page 72
                Size of the pretest
                    Page 73
                Information checking
                    Page 73
                    Page 74
                    Page 75
                Time difficulties
                    Page 76
            Selecting and training interviewers
                Page 77
            Verifying primary data
                Page 78
            Verifying and using secondary data
                Page 79
                Page 80
                Page 81
            Summary
                Page 82
        Data utilization: What does it all mean?
            Page 83
            Page 84
            Page 85
            Flexibility of interpretation
                Page 86
            Meaning of the results
                Page 86
                Page 87
                Page 88
                Page 89
                Reliability of results
                    Page 90
                    Page 91
                    Page 92
                    Page 93
                    Page 94
            Presentation of results
                Page 95
                Page 96
            Summary
                Page 97
                Page 98
                Page 99
    Reference
        Page 100
        Page 101
        Page 102
        Page 103
        Page 104
        Page 105
        Page 106
    An applied research project proposal
        Page 107
        Page 108
        Page 109
        Page 110
        Page 111
        Page 112
        Page 113
        Page 114
        Page 115
        Page 116
    Back Cover
        Back Cover
Full Text
HILDEBRAND-CLASS COPY


1 d (" $ i (9





PLANNING AND
CONDUCTING
APPLIED RESEARCH



By
Chris O. Andrew
Peter E. Hildebrand


hiS
L~4~ '1













PLANNING AND
CONDUCTING
APPLIED RESEARCH




By
Chris O. Andrew
Peter E. Hildebrand


Department of Food and Resource Economics
Institute of Food and Agricultural Sciences
University of Florida


MSS Information Corporation
655 Madison Avenue, New York, N.Y. 10021
























Library of Congress Cataloging in Publication Data

Andrew, Chris O
Planning and conducting applied research.

Bibliography: p.
1. Research Methodology. I. Hildebrand, Peter E.,
joint author. II. Title.
Q180.55.M4A5 001.4'2 75-45131
ISBN 0-8422-0534-9







Copyright @ 1976
MSS Information Corporation
All Rights Reserved











TABLE OF CONTENTS


Preface. . . . . ... . v
Forward. . . . . ... . vii
Acknowledgments. . . . ... ... ix
Chapter I:
INTRODUCTION. . . . . 1
Applied Research . . . 3
The Book . . . . 5


PART ONE: PLANNING APPLIED RESEARCH


Chapter II:
EFFECTS OF RESOURCE AVAILABILITY ON APPLIED
RESEARCH. . . . .. ... 9
Information Resources. . . ... 11
Secondary and Primary Information .. 12
Time Series and Cross-Section Data. 13
Experimental and Non-Experimental Data. 14
Human Resources. . . . ... 15
Physical Resources . . ... 16
Financial Resources. . . .. 17
Time Constraints . . .... 17
Summary. . . . . ... 18
Chapter III:
ORIENTATION AND FOCUS OF PROJECTS: RESEARCHABLE
PROBLEMS, HYPOTHESES, AND OBJECTIVES. . ... 19
A Conceptual Model . . ... 19
Specification of a Researchable Problem. 22
Problems Reflect Felt Needs . .. .23
Problems are Non-hypothetical . 24
Problems Suggest Meaningful, Testable
Hypotheses . . . 25
Problems are Relevant and Aanageable. 25






Researchable Problems vs. Problematic


Situations..


. . . . 26


. . 27
. . 31
. . 32
. . 33
. . 38
. .. 41


. . 46
. . 47
. . 48
. . 52
. . 56
. . 58
. . 62


Examples of Problem Statements. .
Formulation of the Hypotheses. .
Characteristics of Hypotheses .
Some Examples of Hypotheses .
Delineation of the Objectives. .
Summary. . . . .


PART TWO: CONDUCTING APPLIED RESEARCH


Chapter IV:
EXPERIMENTAL DATA COLLECTION. .. ..
Experimental Design. . .
Relationship to the Problem
Relationship to Resources
Secondary Experimental Data. .
Multi-purpose Experimentation.
Summary. . . .


Chapter V:
NON-EXPERIMENTAL DATA COLLECTION. . . 64
Selecting Respondents. . . ... 65
Designing the Questionnaire. . . ... 67
Difficulties in Interpretation and
Communication . . ... 68
Designing for Data Retrieval. . .. .70
Pretesting the Questionnaire . ... .72
Size of Pretest . . ... 73
Information Checking. . . ... 73
Time Difficulties . . ... 76
Selecting and Training Interviewers . ... .77
Verifying Primary Data. . . . ... 78
Verifying and Using Secondary Data .. ... .79
Summary . . . . ... .82
Chapter VI:
DATA UTILIZATION--WHAT DOES IT ALL MEAN?. . ... 83
Flexibility of Interpretation. . ... 86





Meaning of the Results. . . ... 86
Reliability of Results. . . ... 90
Presentation of the Results. . . ... 95
Summary . . . . . 97
References . . . . . . 100
Appendix .................. . ... ...... 108











PREFACE


This book is the culmination of a group effort to
eliminate a deficiency made evident during the organiza-
tion of a graduate course in research methodology at the
UN-ICA Graduate School in Agricultural Sciences in Bogo-
ta, Colombia.1 The deficiency revolved around the dif-
ficulties in organizing research projects oriented toward
real world problems and formulated so that 1) the research
can be completed within the available period of time, ahd
2) the results will be usefulin helping to resolve the prob-
lem toward which the study is directed. It became obvious
2
to a group of agricultural economists working with the
graduate program that the various standard approaches to
the presentation of research methodology are not success-
ful in helping students become efficient researchers con-
sistently able to make meaningful contributions to the res-
olution of agricultural and related problems of their coun-
try.
Initially the efforts of Michael Steiner who was re-
sponsible for the methodology class and of James Driscoll,*
Chris Andrew, and Peter Hildebrand, whowere helping in the



1The graduate school is jointly administered by the
National University of Colombia (UN) and the Colombian Ag-
ricultural Institute (ICA). Beside the graduate school,
ICA has responsibilities in research and extension as well
as service activities such as control of agricultural chem-
icals and port sanitation.
2This group consisted of several Colombian agricultural
economists with ICA including those mentioned in the acknowl-
edgements and agricultural economists with the University of
Nebraska Mission in Colombia. This technical assistance team
worked with ICA,National University and the Graduate School
from 1967 to 1972.




development of the material, focused upon newmeans of pre-
senting the requisites for successful research in a manner
that would have real meaning and utility for the students.
Thus, the core idea now presented in Chapter III germinated.
The topics are not new; most research methodology material
discusses research problems, hypotheses, and objectives.
It is the means of fitting these parts together into a more
useful form which is new. During several courses and while
counselling students and fellow staff members of ICA in re-
search, we were able to revise and improve the concepts.
We found at the same time that this approach to planning and
executing applied research could be easily understood and
used. As the success of the approach became clearer, we de-
cided that it was worth the time required to present it in
book form for a wider audience.
In developing the book, to which all four of us ini-
tially contributed, we found that, although it was relative-
ly easy to use the approach in training students and coun-
selling researchers, it was difficult to present the approach
in a form understandable and usable by persons with whom we
would have no direct contact. Because of our various com-
mitments and spatial separations it became increasingly dif-
ficult for all four of us to coordinate our efforts, so fi-
nally Andrew and Hildebrand assumed the responsibility for
the long process required to convert the vague ideas and
concepts into a form which could be readily conveyed to
students, researchers, and others.












FOREWORD


The basic theme of this book is that of applied re-
search as a service to a client with a problem for which
the information obtained by research can help resolve.
Because applied research has a definite purpose, there is
usually a time constraint or deadline within which the work
must be completed as well as a limit on the other resources
the client has available or is willing to use in the reso-
lution of the particular problem. Consequently, the re-
searcher must be cognizant of the efficient use of the re-
search resources while at the same time functioning so as
to maximize the likelihood of providing a useful product
to the client.
Besides the approach to applied research (covered in
the book), another important factor affecting the success
a researcher will experience in serving his clients is the
research environment within which he labors. An applied
researcher cannot be effective in satisfying clients when
he is isolated from them by a system that reduces or pre-
vents effective communication among them. This can happen,
for example, when an extension service with direct client
contact has little communication with research personnel
even though they may be in the same organization. It can
also happen in research organizations in which projects
are dictated by administrators who have little contact
with the clients and hence have no appreciation of their
real problems. This may be an argument for maintaining only



See [2,30,38,60,61,65,69,75,80,82,86,87,88] forread-
ings onthe role and impact of institutions in the research
process.





small research organizations, but more realistically, it is
an argument for an organization in which the researcher main-
tains close personal contact withthe clients and where he in
turn shares in determining the research priorities of the or-
ganization. We suggest that a better coordinated working re-
lationship between research administrators, researchers, and
clients will develop if all three groups understand the ap-
proach to problem identification which is presented in this
book.
Although a majority of the examples are authentic, and
are drawn from Colombia where most of the writing was done,
the research difficulties presented are not unique to that
country;.they are encountered throughout the world including
the United States. Our desire is to provide the researcher,
wherever he may be,with an approach to research under vari-
ous time and resource limitations which will help him be of
greater service to his clients. This is particularly true
in developing countries where applied research is so needed.


viii













ACKNOWLEDGMENTS


To acknowledge the assistance of each individual for
comments presented during numerous discussions and on the
seemingly endless series of drafts leading to this book is
impossible. Without the early dedication and ideas and
comments by Mike Steiner (presently with the Armor Food
Company) and Jim Driscoll (presently with the Economic Re-
search Service of the United States Department of Agricul-
ture) this book would not have been initiated nor, possi-
bly, completed. Two Colombians, Juan Acosta and Ramiro
Orosco, at the Colombian Agricultural Institute (ICA) de-
serve special recognition for reviews of the material and
constructive criticism, and for using concepts and early
drafts in the classroom. Likewise to Rafael Samper, De-
partment Head in Agricultural Economics at ICA, and his
staff, gratitude is due for sustained interest and encour-
agement.
Ideas and most of the drafts for the book were forth-
coming while the authors were under contract with the Uni-
versity ofNebraska at the Colombian Agricultural Institute
and the National University of Colombia. This contract,
funded by the Ford Foundation and the USAID, helped develop
the agricultural economics profession in Colombia including
three undergraduate programs, a graduate program, and both
research and extension programs. To our colleagues, and to
students at these institutions, we offer sincere acknowledg-
ments and hope that the book will be useful to them.
We express our appreciation for assistance received
from the Food and Resource Economics Department at the Uni-
versity of Florida. To Fred Prochaska andhis students who





have used the text for two years in the research methodol-
ogy course, we are grateful for constructive criticism.
Special recognition is due to Leo Polopolus, Chairman of
the Food and Resource Economics Department, and W.W. Mc
Pherson, Graduate Research Professor, for reviews and con-
sultation. Special appreciation is extended to Beth Davis
for supervising preparation of the final manuscript for
printing.
Also, we extend our appreciation to theMinistryof
Agriculture of El Salvador, where the second author was
stationed on a technical assistance contract, for transla-
tion and preliminary publication of the manuscript in Span-
ish. For final reviews of the Spanish translation and pre-
paration ofthe final manuscript for printing, gratitude is
extended to the Guatamalan Institute of Sciences and Agri-
cultural Technology where the second author is presently
employed.
Lastly, we want to express our sincere gratitude to
our families who shared their time for numerous weekends
and nights with an idea which may have seemed vague and
boring.











Chapter I


INTRODUCTION


About midmorning, the Minister of Agriculture is just
completing a phone conversation as the door to his office
opens to admit one of the young men in the research group
from the Planning Department of the Ministry. At about the
same time the Vice Minister and the head of planning enter
and the four men seat themselves around a small conference
table. The Minister opens the meeting, directing his com-
ments to his Vice Minister: "I'm told that we have a final
report on that project onimpbrting fertilizer, that's great.
It's just in time. Now we ought to be able to convince the
import-export people that they can't reduce our request for
fertilizer and still expect us to meet our new trade commit-
ments. "
Turning to the young researcher, the Minister says en-
couragingly, "OK, young man, they tell me you've made an
excellent study. Now tell us exactly how much fertilizer
is it going to take over the next five years to meet our
production targets?"
"Sir?" replies the researcher, apparently a little
confused.
"Come, come, now, don't be nervous. Just tell us
about the research you've been doing. What are the results?"
The Minister realizes the researcher may be a bit timid.
"Oh, yes sir," smiles the researcher, "thank you."
'Well, as soon as we got your request for information
on the importance of fertilizer, we checked to see what da-
ta we had on Japan and some other countries where there
have been recent increases in production. We thought this
ought to give us some good ideas about the relationship





between fertilizer use and crop production. Here, sir, we
have a series of graphs showing the correlation between
these two variables for a number of countries."
"Yes," replies the Minister, "it's quite evident that
fertilizer is important in increasing crop output. Now,
how much are we going to need?"
The researcher continues, "According to the latest
census, which unfortunately is several years old as you
know, only about 40 percent of our farmers are using any
fertilizer. This is considerably below the rate in the
other countries I mentioned. And in those countries income
per farm family has been increasing rapidly, again demon-
strating the importance of fertilizer." The minister nearly
interrupts but lets the researcher continue. 'Now if we
want to double the number of farmers using fertilizer, we
might be able toassume that we need twice as much fertili-
zer as now. "
'Yes, Isuppose" replies the Minister, "but what about
the land area involved and what about the requirements for
the different crops?"
The researcher, thumbing back through his report an-
swers, "We don't have any information on area of each crop
that is fertilized but cotton and sugarcane consume about
80 percent of the fertilizer used and..."
He is interrupted by the Minister who says, "But don't
you have any estimates of the quantities required to get
the production we need over the next five years? Our prob-
lem is that they want to cut back on fertilizer imports to
help domestic fertilizer production just at the time we
have to try to increase crop production in a big hurry.
We need to know how that could affect our program and how
much importation we need to ask for." Turning to the head
of the planning group he says, "I thought we discussed this
pretty thoroughly that day it came up. What happened?"
'Well, that's right, and I knew we were going to have
a hard time convincing them how important fertilizer was in





our program and I know we talked about that in my office,
didn't we?" the head of planning asks the young researcher.
"Yes, sir," replies the young man, "we knew we had to
get you some good information on the importance of fertil-
izer and that's why I have this information on Japan and
those other countries. "
'Well," replies the Minister, "that's not going to be
much help in solving our problem. We have the meeting with
them tomorrow. But maybe we could hold off a decision for
a couple of days if you think you can get me the information
we need by that time. Why don't you call someone at the
experiment station? Maybe they canhelpyou. But you better
get going. Don't forget how important fertilizer is to us."




There are several important points in this dialogue,
which though fictional, represents a real-life situation
encountered much too frequently. The most important point
is that after waiting right up to the deadline, the Minis-
ter, who is the client, did not obtain the information he
needed for meeting of great importance. As a result, the
research costs incurred by the Planning Department for this
project yielded little of value. The most serious conse-
quence, of course, is the cost associated with not having
the relevant information for the meeting. Although some
of the reasons for the unfortunate situation are evident
in the dialogue, others are more subtle. Regardless of
the reasons, we hope that with this book we can contribute
to the more effective use of research resources and help
prevent the kind of unhappy discussion as that between the
Minister and the researcher.


Applied Research


Research is the otdetly ptocedune by which man in-
crea.ses his knowledge and is conttasted to accidental





discovery because it fottowm a series o steps designed
ptecilsely 6o& the putpose o6 developing information.
Knowledge gained by research may be used by man to produce
a greater abundance of food and fiber, to lighten the bur-
dens of his labor, or in any number of ways to generally
improve his well being. Or new knowledge may simply be
added to man's store of concepts about the universe to await
application at some future point in time. Research under-
taken specifically for the purpose of obtaining information
to help resolve a particular problem is applied research.
Foraresearch undertaking to be applied research it is not
necessary that the results (the new knowledge) in fact re-
solve or help resolve the problem which initiated the proj-
ect (though hopefully they will), but it is necessary that
the research have a specific problem orientation. It is
this kind of research -- that oriented toward resolution
of specific problems -- toward which this book is directed.
The development of Mexican or dwarf wheat was the re-
sult of an applied research process oriented toward the res-
olution of a specific problem [72]. Afertilizerexperiment
oriented toward making recommendations to farmers is another
example, as is the work of a government planner trying to
estimate the likely supply response to fertilizer for a
particular commodity under a proposed new program, or the
total fertilizer requirements necessary to reach specified
production goals, as in our dialogue. Determining accept-
ability of newly developed feed concentrate for fattening
hogs in tropical areas on the development of a hand seeder
for steep terrain in primitive areas also would be classi-
fied as applied research. In general, the research refer-
red to in this book is oriented toward providing useful in-
formation to decision makers such as farmers and public ad-
ministrators.
Applied research, such as that just described, is car-
ried out in all parts of the world -- it is a much more


For thoughts concerning the meaning of research and
the scientific method see [9,10,11,12,14,15,19,22,23,24,25,
28,34,39,52,71,73,74,81,83]





widespread activity than basic research which is a necessity
but one that only the wealthiest countries can afford. Most
applied research is conducted under moderate to severe re-
source limitations which necessitate efficiency in the re-
search process. An effective applied research methodology
is directed toward the.e icient use oa available reseatch
reboutces to maximize the probability of achieving meaning-
dual results to help tresove problems. Disappointment in
the results of applied research--a "So what?" response ---
in most instances can be traced directly to the use of an
inadequate and/or ineffective applied research methodology
which failed to correctly identify the problem.

The Book


Perhaps the most critical deficiency in methodology
is the failure to adequately identify the specific problem
toward which the research is to be oriented (as happened
to the researcher in the Ministry). This may result when
the researcher uncritically accepts the problem as stated
by the client or by his spokesman (the "importance of fer-
tilizer" was not the Minister's problem). Another serious
deficiency may occur even after properly identifying the
problem. This is 'the failure to formulate hypotheses and
objectives correctly oriented toward the resolution of the
problem and to use appropriate analytical techniques (what
hypotheses did the Ministry researcher use?) The most
critical concepts and the interrelationships among problem
identification, hypotheses, objectives, analytical tech-
niques, and resource restraints.
The role of theory, though not developed within the
main text, is also critical to applied research. Without
discounting the value of practice and experience, the
greater the command of theory possessed by the researcher,
the broader will be his capabilities and the more efficient
he will be in planning and conducting the applied research
project. This is true because theory envelopes and supports




2
the entire research process. Without a good command of
stress theory an engineer cannot properly design nor effi-
ciently build a safe bridge. A plant breeder must under-
stand the theory of genetics before he can hope to effi-
ciently develop a strain resistant to a certain disease.
An agricultural economist cannot determine an optimum farm
organization without knowledge of production economics
theory.
The researcher's foundation in theory provides the
orientation for defining a problem that is researchable
within the discipline or disciplines involved in the re-
search and with the resources available. Theory also pro-
vides the basis for the formulation of hypotheses and in
the selection of the analytical techniques to be used.
And it should be obvious that the interpretation of the
results depends heavily on the theoretical orientation of
the researcher.
Although theory permeates the entire research process,
in applied research, frequently conducted under sub-optimum
conditions, the researcher's practical experience is equally
important. Institutional and budgetary restraints, less
than ideal field conditions, poorly trained personnel, in-
adequate background information and other similar factors
have a very significant effect on the research process and
therefore must be recognized and dealt with accordingly.
Practical experience is invaluable in helping the research-
er overcome the obstacles which are so often encountered
in applied research. In all phases of the material to be
presented, the difficulties associated with sub-optimum
research conditions under which the individual research is
apt to be working are considered.
In this book, we have divided the topics into sepa-
rate chapters and the chapters into two parts derived from


For literature concerning the role of theory in re-
search see [20,35,40,53,62,63,70].





the book title; a convention towhich we adhere, though not
without some reservation. Neither section nor the material
in any chapter is independent.
Planning activities are discussed in Part I of the book.
In planning the research project, one must always take cog-
nizance of the means available for conducting the research,
and during the research process it maybe necessary to mod-
ify portions of the original plan. Each of the activities
is affected by the others and by the research resource re-
straints under which the researcher is toiling. The kinds
and sources of data which will be used and the methods of
analysis will be dictated by the hypotheses and objec-
tives,. but they, in turn, must be finalized only after hav-
ing taken into account the effect of resource conditions on
availability of data and/or analytical competence.
In Part II, Conducting Applied Research, we discuss
experimental and non-experimental data collection, verifi-
cation and interpretation of data, and presentation of
the results to the client.
Because of the deliberate and intense emphasis placed
upon problem identification, the book does not discuss in
detail each basic element of a research project. One should
be cognizant, however, of the interrelated components of a
research project and employ them when planning and conducting
applied research. These essential elements are: 1) a prob-
lem statement accompaniedby sufficient information to jus-
tify the need for research; 2) hypotheses; 3) objectives;
4) budget; 5) the appropriate theoretical and analytical
approach and procedures; 6) data requirements including
sources and procedures for obtaining data; 7) a detailed
work plan showing jobs to be done and time sequences; and
8) the reports to be issued for each audience.


































PART ONE:
PLANNING APPLIED
RESEARCH










Chapter II


EFFECTS OF RESOURCE AVAILABILITY
ON APPLIED RESEARCH


The relationship of research activities to the avail-
ability of research resources is an important difference
between applied and basic research. In much of what is
commonly considered basic research, proposal is prepared,
and if funding is granted the project is initiated. It
normally continues so long as financing is available and
then whatever can be concluded is presented as the results
of the project. Seldom are the results periodically scru-
tinized to determine their relationship to the proposal be-
cause the urgency associated with solving a pressing prob-
lem is missing. Nor are results frequently weighed against
the use of resources to estimate the productiveness of the
project.
Applied research is more often (though not entirely)
carried out under other circumstances. Because the research v
is oriented toward the resolution of a specific problem,
there is usually a time restraint fixed by the need to make
a decision. Such research is also carried out under vary-
ing degrees of financial restrictions and usually under
rather severe shortages of trained manpower and modern data
proce.asing resources. Another research resource which is
seldom abundant under many conditions of applied research
is published data, other forms of secondary data or reli-
able in6otmation in general. Basic physical facilities
such as means of transportation or land area for research
can also limit the scope of research activities.
In the process of fitting the project to the resource
restrictions, three alternatives are possible; 1) the re-
sources may be expanded to fit the project, 2) the project





may be narrowed to fit within the restriction, or 3) both
may occur within limits. The first alternative is appro-
priate if the level of precision or degree of confidence
desired by the client prohibits a reduction in the scope
of the project. In this case, the client must be prepared
to provide additional resources where the limitations are
critical whether it be in physical facilities, manpower,
funds, additional time for completion, or some combination
of these provisions.
If resources cannot be expanded for particular proj-
ect and the deadline for conclusion is firm, the researcher
has four further possibilities open to him. First, he may
study fewer variables, ignoring some relationships which
affect the analysis, but those which he hopes are less im-
portant than the ones included. Second, he may also aggre-
gate variables into groups. In this manner, it is possible
to include those relationships which may otherwise have been
omitted, but the nature of the relationships, because of the
aggregation, becomes less clear. A third alternative is to
modify or change the nature of the analysis to be carried
out. Less complex analyses can usually be conducted more
rapidly and with fewer facilities, but the precision of
the results is reduced accordingly. Finally, the researcher*
may choose to make fewer observations either in the form
of fewer experiments or a reduced sample.
It is clear that resource availability has an impor-
tant effect on the nature of the research product derived
and the level of precision which can be achieved *or the
level of confidence which can be placed in the results.
Even in very limited resource situations, however, decisions
are necessary and researchers are expected to provide use-
ful information. The ultimate decision as to the quantity
of resources to be made available for any particular proj-
ect and the time limit for its completion rests with the
client, or with the person responsible for making decisions
related to the resolution of the problem toward which the
research is oriented. At the same time, the client de-





pends on the researcher to provide him with accurate mea-
sures of resource requirements and the scope and precision
which he can expect from devoting different amounts of re-
sources to any particular project.
The following sections will describe the principal
research resources and include a general discussion of how
each resource, when restricted, can affect a project. A
single chapter does not adequately cover the range of al-
ternatives open to the researcher and his client, but we
hope that it will provide sufficient stimulus so that the
researcher, with imagination will be flexible in adapting
his research efforts to any resource situation.


Information Resources


Information is the foundation upon which research is
based; hence, one of the major tasks of the researcher is
collection of information for use in the research process.
Information in general and data specifically are as crit-
ical to the problem identification phase of the project
as they are to analysis. Their availability profoundly
affects both the quantity and quality of research which
can be produced within a given period of time. There are
few limits to the quantity of data that can be accumulated
given sufficient time and resources, however, requirements
are narrowed and brought into focus by careful research
planning.
In general, published information provides the basis
for problem formulation while either published data or
data generated in the research process (or both) may be
the source of information for analysis. Published data,
or any information not generated or accumulated under the



1See [2] for a discussion concerning allocation of
scarce resources to alternative research programs and proj-
ects.






control of the researcher but utilized in the particular
project are considered to be secondary data. In contrast,
any data generated by the researcher and directly associ-
ated with the research project are primary data. Another
classification of data which has an importance to research
is that which differentiates time series data, or observa-
tions made at specific intervals over a period of time,
from coss-s4ection data which are taken at one point in
time. A third comparison is that between experimental
and non-expeAimentat data. Each of these kinds of data
or data sources has different costs associated with avail-
ability and analysis, and each has different implications
with respect to confidence in conclusions based upon it.


Secondary and Primary Information


When secondary information related to the project is
available, its cost to the researcher, both in terms of
time and money,is usually less than that required to obtain
the same kind of information first hand. However, the use-
fulness of secondary data as a research resource is not al-
ways as great as that of primary information. The researcher
must always select the appropriate primary secondary data
mix and the techniques used to combine the two in order to
obtain the most useful research product within the limits
of his other resources.
For practical purposes, some data are only available
from secondary sources. Price series, crop production
series and census information are examples. It is simply
not appropriate to consider obtaining this kind of infor-
mation first hand. But it does not follow that available
secondary data of this nature are always adequate, repre-
sentative, or even relevant to the particular project.
The researcher must satisfy himself that any particular
series really measures something that is relevant to the
project or something which can be made relevant through
acceptable modifications or manipulation. If care is not





taken to verify secondary information in this manner, the
researcher may well draw false conclusions from his analy-
sis of the data.
Primary data usually will be more closely related to
a particular project than secondary data which are collect-
ed for a multitude of purposes or for projects with other
objectives. But primary data collection almost always re-
quires more time than isnecessary when using secondary da-
ta, and may require more of the other resources. Hence,
although primary and secondary data are not necessarily
substitutes for each other, the researcher should be aware
of the availability of secondary information and assess its
relevance as an alternative to the collection of primary
data.


Time Series and Cross-Section Data2


Time series data, as the name implies, are data ob-
tained in a series over a period of time. Examples are
price series,production and acreage data, and indices of
costs of living or wages, most of which must be accumu-
lated over long periods of time to be useful. Cross-sec-
tion data are those taken at a fixed point in time (or
over a relatively short period of time) and include ob-
servations of several different strata or levels of a
population. In many cases, time series data are essential
to a project, but occasionally, cross-section information
can be substituted. Time series data of consumption and
income may be used to study the same relationship at a
given point in time. Because, as in this case, cross-sec-
tion data can substitute for a time series, the researcher
should not despair if time series is not available. Nor,
by the same token, should he blindly use the time series
without considering the advantages of obtaining and using
the cross section data. Or in some cases it might be desirable
to use a combination of the two.


2For a brief discussion of how these two types of data
influence demand analysis as one example, see [64].





Experimental and Non-Experimental Data


Experimentation is a means of obtaining data with
relatively high precision in measurement of the variables.
In many instances this precision is associated with a
longer time requirement than that needed for obtaining non-
experimental data. In crops minimum of one season is re-
quired and much longer periods may be needed if, for exam-
ple, effects of weather are to be determined. A year or
more may be common for some animal experiments. When, as
discussed in Chapter I, the Minister requested that the re-
searcher check with someone at the experiment station to
help resolve the fertilizer demand question, he was hoping
that secondary experimental data might provide specific
crop requirement guides to be used in preparation of a de-
mand estimate. He knew time would not permit the design
and analysis of crop experiments.
In some cases, however, experimentation can reduce
the time and resources required to resolve a particular
problem when compared with non-experimental data collec-
tion. For example, an experiment to determine potential
consumer acceptance of a new product before it is marketed
can be less time consuming, require fewer resources and in-
volve less financial risk for an industry than consumer
response research following the full scale production and
marketing of the product.
A possible alternative to experimentation is the col-
lection of non-experimental data through survey of a num-
ber of people who have knowledge or experience with the
phenomenon in question. This procedure usually requires
less time, but may be less precise and more costly than
experimental data collection. An approximation of a fer-
tilizer experiment for example, can be made by surveying a
group of farmers, each of whom uses different quantities
of fertilizer. Obviously, results will be less precise
than experimental results, but at the same time, estimates
of variance will be more realistic than from a controlled





experiment so that farmers will have a better idea.of the
range of response to expect from the use of fertilizer.
Another non-experimental source of information in the
context of applied research is the simulation of results
through the use of "best guesstimates" of the most knowl-
edgable people available to the researcher. In some ways,
this is similar to an informal survey. For instance, suf-
ficiently detailed input requirements, yields, and resource
restrictions can be generated in this manner for use in pre-
paring budgets, and ultimately a linear program or simula-
tion model for the agricultural sector of region. Such a
model, while less valid than could be possible under more
optimal conditions, can be used successfully in project
planning where time limits prohibit experimentation and
current conditions in the area will not provide the detailed
information needed from a survey.


Human Resources


As with most resources, the human element must becon-
sidered from the points of view of quantity and quality.
Sheer availability is not sufficient for most research un-
dertakings; the training and capabilities of personnel must
be considered when planning the project. Except in rare in-
stances, the time factor in applied research prohibits the
training of professional personnel though there may be time
to train some non-professionals such as interviewers. A
field hand who cannot read or write may be willing to do
the physical labor of an experiment, but he cannot be relied
upon to maintain records of the results. Nor can profes-
sionals with minimum of training in statistics be expect-
ed to carry out complicated statistical analyses. In the
first case, other arrangements will have tobe made, and in


3Examples are research projects currently underway in
Viet Nam and El Salvador [89] by the Food and Resource
Economics Department, Institute of Food and Agricultural
Sciences, The University of Florida.





the second, less sophisticated techniques will have to be
employed.
A common misuse of research resources exists where el-
egant data collection techniques are employed but the data
are not fully utilized because appropriately trained person-
nel are not available to make proper or correct analyses.
In the short run, simpler experiments and surveys which can
be analyzed readily by available personnel are more appro-
priate. Money saved by not conducting elegant data collec-
tion programsmay be used to train personnel to conduct and
analyze more complicated and sophisticated experiments and
surveys in the future.


Physical Resources


Non-technical physical resources include transporta-
tion facilities, land, office space, machinery, typewriters,
and other items of a similar nature. Like all other re-
search resources, their availability must be considered
when planning the project.
Technical physical resources include scientific instru-
ments, calculators, electronic computers, etc. Certain kinds
of instruments may be indispensable for particular aspects
of project -- some hypotheses may need to be eliminated if
the correct instrument is not available or is too costly
compared to expected results to justify its use. On the
other hand, an electronic computer, while not indispensable,
may substitute for other resources such as money or time.
The use of a computer,when available, sometimes can short-
en the time required to achieve useful results. If a re-
searcher must wait long periods oftime, however, for cards
to be punched and programs to be de-bugged, he may be better
off to undertake appropriate analyses onadesk calculator.
When computers and calculators are unavailable a diligent
researcher might still provide rough but meaningful recom-
mendations based upon experience and imaginative use of the
most basic of physical resources -- a pencil and paper.





Financial Resources


This resource to a certain extent can be substituted
for all the other resources. At the same time it may not
be appropriate, feasible, or even possible to make this
substitution because of other considerations. Nevertheless,
funds are required for almost all research projects and their
availability is an important consideration in research plan-
ning.


Time Constraints


Time is usually not thought of as a resource in the
same terms as physical facilities, information and human
resources, but its effect on the planning and execution of
applied research is similar. Considered as a resource, time
can interact with other resources in that substitution of
one for another canbemade. If a decision on a particular
problem is critical and time is limited, a greater number
of other resources will be required to achieve a given level
of confidence than would be necessary if more time could be
taken. Hence, the use of more time is an effective substi-
tute for quantities of other resources. But also, consuming
more time on one project reduces the amount of that limited
resource which is available to help resolve other problems.
In some situations, time can be overwhelmingly limited.
This is usually the case when one is involved in so-called
"brush fire" research of the type frequently faced by plan-
ning groups within the various ministries of government.
In such instances the researcher must always maximize the
efficiency with which he uses this resource. Only data
readily available can be used and lengthy methods of analy-
sis cannot be considered. Many times "best guesstimates"
are the only means available to the researcher under these
conditions.
Approaching the other extreme are theses at any of
the levels at which they are written in various education





Financial Resources


This resource to a certain extent can be substituted
for all the other resources. At the same time it may not
be appropriate, feasible, or even possible to make this
substitution because of other considerations. Nevertheless,
funds are required for almost all research projects and their
availability is an important consideration in research plan-
ning.


Time Constraints


Time is usually not thought of as a resource in the
same terms as physical facilities, information and human
resources, but its effect on the planning and execution of
applied research is similar. Considered as a resource, time
can interact with other resources in that substitution of
one for another canbemade. If a decision on a particular
problem is critical and time is limited, a greater number
of other resources will be required to achieve a given level
of confidence than would be necessary if more time could be
taken. Hence, the use of more time is an effective substi-
tute for quantities of other resources. But also, consuming
more time on one project reduces the amount of that limited
resource which is available to help resolve other problems.
In some situations, time can be overwhelmingly limited.
This is usually the case when one is involved in so-called
"brush fire" research of the type frequently faced by plan-
ning groups within the various ministries of government.
In such instances the researcher must always maximize the
efficiency with which he uses this resource. Only data
readily available can be used and lengthy methods of analy-
sis cannot be considered. Many times "best guesstimates"
are the only means available to the researcher under these
conditions.
Approaching the other extreme are theses at any of
the levels at which they are written in various education





systems of the world. Often they are not oriented toward
any particular problem so the time factor is not relevant,
but among those that are problem oriented, too often time
is relegated to a secondary role in resource utilization.
As a result, many theses are not written in time to be of
any great use -- their value reduced by failure to account
for the time factor. Those who excuse this fault by em-
phasizing that theses are only meant to be training tools
often deprive the student of an opportunity to perform and
benefit from meaningful research.


Summary


Research undertaken specifically for the purpose of
obtaining information to hblp resolve a particular problem
is applied research. The purpose of this chapter has been
to examine the relationship between the scope of an applied
research project and the quantity and quality of research
resources which canbe devoted to the solution of the prob-
lem at hand. The urgency of problem resolution makes time
an important resource or constraint which interacts with
the other financial, human, physical, and information re--
sources.
The researcher must be aware of the effect that cer-
tain resource limitations can have on his research. This
cognizance will improve his research effort by increasing
the probability that the proposed project will produce use-
ful results. Projects designed in the absence of this con-
sideration can and frequently do run into difficulties such
that the productive potential of the resources utilized is
not attained. The result is that less effective information
is made available for decision making and problem resolution.
Careful consideration of resource availability can help pre-
vent situations where the deadline arrives and the researcher,
still engrossed in gathering data or making analyses, has
little of value to report to his client.









Chapter III


ORIENTATION AND FOCUS OF PROJECTS:
RESEARCHABLE PROBLEMS, HYPOTHESES, AND OBJECTIVES


Proper management of applied research requires clear
definitions of the goals to be achieved through the project.
16 one does not know otr what he issttiving he cannot hope
to effectively accomplish the task. Orientation and focus
of the project include the specification of the problem in
terms which make it amenable to research, the formulation
of hypotheses which are subject to being tested, and the de-
lineation of the specific objectives which the project should
accomplish. The interaction of these three phases and their
clear exposition serve as a plan or guide for determining
the procedures to be followed by the researcher in conducting
the research. Adequate orientation and focus of the project
will help assure that it can be completed satisfactorily with-
in the resource limitations facing the researcher and will
also serve to explain the nature of the undertaking to the
client or the administrators for whom the research is being
undertaken.


A Conceptual Model


We have found it useful to consider the process of plan-
ning the applied research project as being equivalent to a
funnel with a series of filters (Figure 1.) Such a funnel
is used to reduce a large volume of liquid to manageable
proportions. The orientation and focus of research proj-
ect serves the same purpose -- it reduces large volume of
information to manageable proportions. Extraneous informa-
tion and ideas are eliminated as foreign matter might be fil-
tered in the funnel. Each part of the' project statement--









Chapter III


ORIENTATION AND FOCUS OF PROJECTS:
RESEARCHABLE PROBLEMS, HYPOTHESES, AND OBJECTIVES


Proper management of applied research requires clear
definitions of the goals to be achieved through the project.
16 one does not know otr what he issttiving he cannot hope
to effectively accomplish the task. Orientation and focus
of the project include the specification of the problem in
terms which make it amenable to research, the formulation
of hypotheses which are subject to being tested, and the de-
lineation of the specific objectives which the project should
accomplish. The interaction of these three phases and their
clear exposition serve as a plan or guide for determining
the procedures to be followed by the researcher in conducting
the research. Adequate orientation and focus of the project
will help assure that it can be completed satisfactorily with-
in the resource limitations facing the researcher and will
also serve to explain the nature of the undertaking to the
client or the administrators for whom the research is being
undertaken.


A Conceptual Model


We have found it useful to consider the process of plan-
ning the applied research project as being equivalent to a
funnel with a series of filters (Figure 1.) Such a funnel
is used to reduce a large volume of liquid to manageable
proportions. The orientation and focus of research proj-
ect serves the same purpose -- it reduces large volume of
information to manageable proportions. Extraneous informa-
tion and ideas are eliminated as foreign matter might be fil-
tered in the funnel. Each part of the' project statement--




















P'toWematic Situation
Hbazhe in ac2t)


Reseatchabte Phobte

Hapoathe6 e-6


Available


-I-


I Plan o6 Execution

Figure 1.--Fitting the research project to the resources.





problem, hypotheses, objectives -- serves to narrow down the
proposal, to bring it into sharper focus, and to filter out
surplus or unrelated information to make the orientation more
precise. One can consider the size of the lower opening of
the funnel as beingdeterminedby available research resources
(the bottleneck). Hence, the proposal as it finally emerges
must fit within these resource restrictions.
The top of the funnel will be the general subject matter
orientation of the researcher. The research willbe within
the area of interest of the individual researcher and usually
related to his. individual talents. The general problematic
situation will fall within these limits, but any problematic
situation suggested by a client may contain several research-
able problems. Hence, the selection of a researchable prob-
lem based upon the client's needs is equivalent to sharpening
the focus ona particular aspect of the more general proble-
matic situation. Hypothesis formulation narrows the problem
to tentative relationships which will be tested in the re-
search process. Finally, the objectives specify the limits
within which the project will be conducted and describe the
useful product which will result.
Obviously, information, ideas andrelationships do not
flow through the funnel like water but are filtered time and
again. The process ofmoving from the top to the bottom of
the research project funnel requires push and pull, pare and
adjust, specify and redefine until the proper proportions
are achieved. The problem, the hypotheses and the objectives
may each have to be changed and adjusted many times before a
satisfactory product results.
At this point, word of caution is in order. The re-
sult of this funnelling process should be a plan of execution
that has high probability of accomplishing research which
will be helpful in resolving the problem toward which the
research is to be directed. It is much too common, and seem-
ingly easier, to embark on the next steps of the research
process -- data collection, analysis, and interpretation--
with a poorly specified project statement. The consequence





is usually that budget and time restrictions cannot be met
and one of the following results:
1) Conclusions must be drawn on the basis of in-
adequate evidence,
2) More resources and more time must be devoted
to the project to allow completion, or
3) The project withers and dies and is relegated
to a drawer in the file, never to be heard from
again.
No matter what fate the research meets, the return on
the investment in the project willbe lower than necessary.
To avoid these consequences, careful orientation and focus
are essential and can well be the most productive time spent
on the entire project.


Specification of a Researchable Problem


Problem specification, or elaboration of a problematic
situation in such a way that it presents a researchable
problem, is a vital step in the process of applied research
[42, 84]. Seldom is client's problem defined for the re-
searcher so that the requirements of the research process
are obvious. Even in cases where it may at first appear
that it is so defined, it usually is not the case. A com-
mon and deceptively simple appearing example is the problem
of determining crop production costs. An economist cannot
uncritically accept a "cost of production" project without
understanding which specific cost components are of inter-
est to the client. The researcher, because of his training,
will usually have a greater appreciation for the technical
characteristics of the problem than will the client and
should therefore consider it part of his responsibility to
identify symptoms and diagnose the problem. He should
perceive the identification of the problem as major task.1


For a discussion of various attitudes toward problem
identification in research see [68,77,79].





On the other hand, the researcher cannot assume that he au-
tomatically understands the problem better than does the
client. The researcher must work with the client until they
have jointly defined an acceptable and researchable problem.
Problem specification is nota simple process. Hildreth
and Castle summarized a discussion concerning problem identi-
fication as follows:
"The start of research is the most
important and difficult stage of
research. It requires far more than
logic; it includes procedures which
cannot be neatly categorized and com-
municated." [56]
But there are several characterisitcs which a project state-
ment will possess if it defines a researchable problem within
the context of applied research. These characteristics of a
problem statement are that problems reflect felt needs, prob-
lems are non-hypothetical, problems suggest meaningful and
testable hypotheses, problems are relevant and manageable,
and aresearchable problem differs from a problematic situ-
ation.


Problems Reflect Felt Needs


A problem exists when there is a need felt by a client.
This client may be an individual, a group, or a society.
The need must be "felt" in the sense that the originating
party believes that change can be realized, and it may arise
from social tensions, doubts, conflicts, failure to realize
goals, concern for an anticipated occurance which might be
preventable, or the simple lack of knowledge if this knowl-
edge is necessary to contribute directly to the resolution
of another felt need. To be appropriate as a researchable
problem, the need must be amenable to change as a result of
the information supplied by the research process. Hence,
all felt needs are not necessarily functional so far as per-
mitting the formulation of aresearchable problem statement.





Problems Are Non-hypothetical


A researchable problem statement must be based on fac-
tual evidence. The relationships expressed can be neither
hypothetical nor subject to doubt or question in the mind
of the researcher. The researcher must use his judgement
as he sifts through available information to determine to
his satisfaction what are andwhat are not acceptable facts
and factual relationships. In a probability sense,of course,
few facts can be accepted with complete confidence. However,
the facts or factual relationships accepted by the client and
the researcher in the problem statement must be such that
testing of their validity is unnecessary. If a particular
proposition cannot be accepted as fact, then if it is rele-
vant to the case, it must be relegated to the status of a
hypothesis.
All researchers and their clients will not accept the
same information as facts of factual relationships because
individual judgements, knowledge and experience affect this
choice [5]. In defining the researchable problem related to
a shortage of manufactured dairy products, one researcher,
because ofhis experience and general knowledge, maybe wil-
ling toaccept the proposition that there is no shortage of
milk processing equipment in a particular area. For him
this forms part of the problem statement. Another researcher
may feel that the validity of this proposition is not clear,
so in the second case, it must become one of the hypotheses
(if it is relevant to the problem). Obviously, the nature
of the research project will be different in each case.
This is the stage of the research 'process in which a
review of literature is most productive. By means of this
review the researcher seeks to utilize the experience of
others to help in the orientation of the project. It should
be apparent that this kind of orientation can change the
focus of the research effort and can have significant im-
pact on the productivity of the research resources.





Problems Suggest Meaningful, Testable Hypotheses


Because the statement of the problem serves to orient
the entire research process, it must suggest testable hypo-
thetical relationships. Hypotheses are formulated as par-
tial explanations ofthe unknown relationships which create
the problem, and those which cannot be tested will be of
little assistance in the resolution of the problem. Hypo-
theses are testable when information about their validity
may be collected and analyzed.
The hypotheses must also be developed from the prob-
lem statement in a manner which does not result in trivial
solutions. Triviality indicates a tautology, an obvious
solution, or an infeasible solution. The hypothesis that
"per capital consumption of food products is low because
there are too many people," derived from a problem state-
ment referring to the existence of hunger in a country is
such a hypothesis. Even if the hypothesis is substantiated,
it results in an answer which is of little or no use in the
alleviation of the immediate felt need.
If the problem statement does not suggest testable hy-
potheses for resolution of the problem under investigation,
the researcher has not adequately formulated the problem
for research.


Problems are Relevant and Manageable


Agricultural scientists tend to work at extremes.
"They tend to work either on problems where the outcome
is highly predictable but which has little impact on prob-
lems or on problems so large as to be unmanageable"[56, p.
38].
This comment was made with reference specifically to
agricultural economists but it applies to other disciplines
as well. An agronomist designing an experiment to determine
yield response on a certain soil, even though information
about similar soils is readily available, is an example.





Problems Suggest Meaningful, Testable Hypotheses


Because the statement of the problem serves to orient
the entire research process, it must suggest testable hypo-
thetical relationships. Hypotheses are formulated as par-
tial explanations ofthe unknown relationships which create
the problem, and those which cannot be tested will be of
little assistance in the resolution of the problem. Hypo-
theses are testable when information about their validity
may be collected and analyzed.
The hypotheses must also be developed from the prob-
lem statement in a manner which does not result in trivial
solutions. Triviality indicates a tautology, an obvious
solution, or an infeasible solution. The hypothesis that
"per capital consumption of food products is low because
there are too many people," derived from a problem state-
ment referring to the existence of hunger in a country is
such a hypothesis. Even if the hypothesis is substantiated,
it results in an answer which is of little or no use in the
alleviation of the immediate felt need.
If the problem statement does not suggest testable hy-
potheses for resolution of the problem under investigation,
the researcher has not adequately formulated the problem
for research.


Problems are Relevant and Manageable


Agricultural scientists tend to work at extremes.
"They tend to work either on problems where the outcome
is highly predictable but which has little impact on prob-
lems or on problems so large as to be unmanageable"[56, p.
38].
This comment was made with reference specifically to
agricultural economists but it applies to other disciplines
as well. An agronomist designing an experiment to determine
yield response on a certain soil, even though information
about similar soils is readily available, is an example.





The researcher knows with a high degree of certainty whe-
ther or not a response will be observed.
Over ambition, lack of adequate forethought, and in-
experience are the principal causes of unmanageable proj-
ects. An over-ambitious researcher may be motivated by a
desire to study all the problems in a given sector so that
he can answer any question that arises. Or anunmanageable
research project can result from suggestions by clients or
administrators unfamiliar with the discipline of the re-
search. In this case the researcher should not accept the
project without first more precisely defining the problem
and reducing the proposed project tomanageable proportions
within the time requirement and within the human, financial
and other resources available for the project.
An unmanageable research project yields few benefits
to anyone. The most likely result of such a project is
superficial treatment of part of the problem and the ne-
glect of other parts. Little detail will be achieved, and
much that is presented may be found to be inaccurate or in-
sufficient. The contribution of this type of study will
almost always be less than that of a more specific study
which examines fewer phenomena, but does soin more detail.


Researchable Problems vs. Problematic Situations


Confusion is likely to exist relative to the differ-
ences between a problematic situation and a researchable
problem. In our context, there is a real and functional
difference between the two. First, problematic situation
is a phenomenon which exists; a researchable problemmust
be identified and defined. A problematic situation repre-
sents a generalized situation but a researchable problem,
expressed in the above terms, must be specific. "An in--
creasing rate of crime in the cities," assuming the state-
ments is true, is an example of a problematic situation-it
exists and it pertains to felt needs. But in no way can
the statement be construed as statement of a researchable





problem. The expression of a problematic situation can
serve as general orientation to the broad area of interest
of a research project, but it is not sufficient to serve
as a guide to a research project.
A problematic situation can be the source of a variety
of researchable problems. Different clients, different re-
search administrators and different researchers are likely
to arrive at a variety of researchable problems from the
same problematic situation. That is to say that there is
no single right, or correct, researchable problem -- there
is only a correct framework within which the researchable
problem must be expressed to be useful to the researcher.
The selection of the researchable problem which will actu-
ally be undertaken will depend on the situation within which
the research is being conducted.


Examples of Problem Statements


In evaluating statements which are considered by their
author to delineate researchable problems, it is difficult,
if not impossible, to determine when deficiencies are due to
lack of care in problem formulation on the part of the re-
searcher or are due to an unclear concept of the nature of
the problem. An example of such a statement is the follow-
ing:2
1) "Rural unemployment created by an increase
in the use of agricultural machinery."
There is no doubt that the author was focusing on a prob-
lematic situation and this interest had to do with unem-
ployment. But it is not clear what specific problem existed
in his mind. The statement does not provide the basis for
a research project though it might spark a lively debate.
As it stands, it does not meet the basic requisites for the.
specification of a researchable problem. Other examples of

2The examples used in the remainder of this chapter
are taken from class papers and research proposals submit-
ted by graduate students in the Department of Agricultural
Economics, Instituto Colombiano Agropocuario, Bogota, Colom-
bia.





incomplete or incorrectly formulated problem statements
are the following:
2) "Few cattlemen vaccinate against hoof
and mouth disease."
3) "Exportation of fresh meat from Colombia."
Let us analyze the above three statements from the
point of view of the requisites necessary for a correctly
specified problem statement. Do they concern a felt need?
Probably all do, but what exactly, is that felt need? The
felt needs suggested by those statements are numerous. Are
the rural unemployed problem from the standpoint of crime
or poverty in the cities, or is the author perhaps consid-
ering those unemployed as a source of inexpensive labor for
rural industry? Is the author (or client) of the second
statement the president of drug company or is he the head
of a meat export company? Is the third statement problem
from the point of view of Colombia, which may be looking for
increased foreign exchange, or, perhaps of Argentina which
may be considering Colombian competition in the world mar-
ket? Each of these points of view suggests a different
problem, and hence, different research project. It would
be folly to initiate research project on any of the above
topics without more complete specification of the client's
felt need.
Are the statements hypothetical or subject to question
in the mind of the author? This is the most difficult test
for a third person to make because he is not aware of the
precise knowledge held by the researcher or client. For
this reason, proper background information in the research
project statement is critical. Not everyone will automat-
ically be convinced that the increased use of agricultural
machinery leads to rural unemployment. However, if such a
relationship is acceptable to both the client and the re-
searcher, and is considered firm and non-hypothetical, it
can be acceptable in the problem statement as a non-hypo-
thetical relationship. The second and third statements do
not express causal relationships and hence are not subject
to this criterion. They are simply incomplete.





Do the statements suggest testable hypotheses? The
first statement could be formulated as a testable hypothe-
sis, but if it is to be accepted as a factual relationship
for problem statement, then it cannot be a hypothesis for
the purposes of the research. Although testable hypotheses
associated with the other two statements could be contrived,
any firm relationship between them and the problem in the
mind of the reader would be purely coincidental.
Another problem statement will be analyzed to deter-
mine if, or how, it might be improved.
4) "Deficient milk production reduces domestic
consumption and makes imports necessary in
this agricultural subsector,"
On the surface this appears to be a more complete problem
statement than any of the preceding. Certainly it repre-
sents a felt need; in fact more than one. Is the problem
to which the author is directing himself a production prob-
lem, one of poor nutrition, because of inadequate quantities
of milk, or is he concerned with the expenditure of scarce
foreign exchange? From the present statement, it is impos-
sible to be sure.
The relationships expressed probably meet the non-hy-
pothetical requisite, though not necessarily. The first
relationship is really a tautology if "deficient" is defined
in terms of domestic consumption. The second relationship
could be hypothetical unless government policy, for example,
has provided for the imports ofmilk to make up deficits in
domestic consumption.
The statement does not legitimately suggest any hypo-
theses except the trivial ones that increased production
would increase consumption and/or reduce the necessity for
imports. And these are not really testable in the usual
research framework. Hence, even though the problem would
be amenable to one or more meaningful solutions, it is prob-
ably not researchable within the usual limits of time and
funds. Several years would be required to determine experi-
mentally if increased domestic production would, in fact,
result in increased consumption.





In order to improve this statement, it is first neces-
sary to focus more precisely on the orientation of the au-
thor with respect to his felt need. It turns out that the
author ofthe statement was concerned with problems of pro-
duction, principally with high costs, low productivity, and
the small profit margins of the producers of milk. His re-
search interest then focuses on the dairy herd and the
dairy farm, and possibly on the farm-to-market process.
Although it will never be possible to determine the exact
nature of a proposed research project from the problem state-
ment alone, amore precise statement is necessary before one
can proceedto formulate hypotheses and specify objectives.
A better formulation of the above statement resulted from
more reflection by the author on his orientation:
5) "The low level of technology on dairy farms
contributes to high costs of production, low
average productivity, and a deficient market-
ing system for milk. These factors cause low
profits to the producer, price fluctuations
for the consumer, and deterioration in the
balance of payments because of the necessity
to import milk."
In this form, the statement implies, in accordance
with the requisites, that the author accepts as fact that
a low level of technology is a causal factor in low pro-
ductivity, high costs of production and a deficient mar-
keting system for the product. Furthermore, he accepts
that these factors cause low profits, price fluctuations
and the necessity of importing milk. By accepting these
relationships as fact, they cannot appear as hypotheses to
be tested by the research process. If the researcher or
his client can not accept any of these relationships as
factual, then the problem statement should be modified and
the doubtful statements submitted ashypotheses tobe tested
(assuming they can be tested within the limits of the avail-
able research resources).




Formulation of the Hypotheses


It is clear that the logical sequence of events in the
process of applied scientific inquiry begins with the ob-
servation of phenomena in the empirical world in common
sense terms. Determination and classification of these
events into problematic situations and specific researchable
problems set the stage for postulating various potential
means of problem resolution. This part of the process in-
volves the formulation of hypotheses which formalize the
premises to be tested by the research effort.
Hypotheses are tentative propositions that must relate
to the problem so as to be helpful in providing means of
resolution. Any suggested or indicated means of resolving
a problem must be formulated so as to be testable and the
relationship to the problem must be evident. To be logically
complete and functional a hypothesis must involve a rela-
tionship. Such a formulation constitutes, implicitly if
not explicitly, a hypothesis inthe form of iZ-then prop-
ositions. The "if" clause describes the relationship be-
tween the postulated condition and the proposedresult.
For example, "If Colombia can increase its beef production
by 15 percentand reduce the costofproductionby 10 percent,
then it can successfully export beef andmeet domestic re-
quirements." The first clause "If Colombia can increase
its beef production by 15 percent and reduce the cost of
production by 10 percent" sets the conditions that must be
met and the remaining clause relates the proposedresults.
Hypotheses are derived from the observations and re-
lationships accepted as, or assumed to be, fact in the
problem statement. They provide the guidelines for the
type of data and techniques necessary for analysis. This
implies that hypotheses are formulated before the data col-
lection activity of the research project has started. In
this sense hypotheses indicate the direction for data col-
lection; hypotheses that are formulated to explain obser-
vations aftertheyare collected may not be useful for prob-




lem resolution. The hypotheses, then, are a necessary link
between the problem and the data collection and analytical
stages of the research.
The basis for correct formulation of hypotheses is the
knowledge of the researcher, this knowledge being founded
primarily in theory. The broader the experience of the
researcher in relating theory to applied problems, the more
efficient he will be in formulating appropriate hypotheses.
Whereas the researcher and the client, jointly, must share
the responsibility for problem specification, it is primar-
ily the responsibility of the researcher, as the expert in
his field,.to formulate the hyptheses.


Characteristics of Hypotheses


Hypotheses appropriate to applied research have the
following characteristics:
1) They must be formed as ii-then relationships
and stated in such a manner that their impli-
cations and relationships to the problem can
be shown logically. The explicit use of the
words if-then is not necessarily required;
the relationship, however, is critical and
often an explicit if-then statement will
assure an accurate relationship.
2) They should be stated as simply as possible
both interms of theoretical complexities and
implications and in terms of number of vari-
ables.
3) They must be capable of verification or rejec-
tion within the limits of the research re-
sources.
4) They must be stated in a manner which provides
direction for the research. The hypotheses,


For this argument and others relating theory to the
research process see [35,45,53,63,73].





when well formulated, will suggest the appro-
priate data and analytical techniques for
testing that should be employed in the re-
search process. Thus, a set of hypotheses
can be thought of as a plan of action.
5) Taken together, they must be adequate and
efficient in suggesting one or more meaning-
ful solutions to the problem. They must
provide for an acceptable level of confidence
in the results, but at the same time economize
in the use of scarce research resources.


Some Examples of Hypotheses


To continue with the proposed dairy study, the fol-
lowing are the hypotheses which were submitted inthe second
draft of the proposal:
1) "Increasing the level of technology and of
physical production and the economy per unit
of exploitation, in association with a reduc-
tion in the costs of production, would result
in stability between supply and demand."
2) "Providing more financial resources for in-
creasing production and restructuring the
market channels would allow simpler price
regulation."
3) "Establishing milk regulations would provide
optimum quality anda price warranted by that
quality."
Although all the hypotheses are generally related to
the problems as stated, it is quite obvious that they encom-
pass a much broader front than we were imagining from the
reformulation of the problem statement. This revelation
leads one immediately to the suspicion that the hypotheses
violate the second requisite of hypotheses -- simplicity.
The first hypothesis encompasses a fair proportion of all
economic theory and certainly does not clearly specify how
one moves from supply to demand with ease. Any reasonably
low-cost means of testing this hypothesis is hard to imagine.
The second and third hypotheses are apparently related to




the problem through the concern with price fluctuations
and, perhaps with the low profits of the producer. However,
the relationship to the problem is only tenuous at best,
and actually introduces new concepts that were not in the
problem statement. Rather than helping to clarify the re-
search proposal, as they should, these hypotheses tend to
add confusion. Clearly, they do not provide direction or
guidance for the research which is one of the primary func-
tions of hypotheses.
Because the author of the hypotheses in the example
did not progress beyond this point, we must now begin to
act as if we were the researcher and formulate the hypothe-
ses according to our understanding of the problem. In-.doing
so, it may be necessary to better identify the problem it-
self (normally done in consultation with the client) so that
the proposal can be improved, but because this occurs many
times in the formulation of a good research proposal, we
will not be wasting effort. Few people are capable of writ-
ing an acceptable research proposal on the first attempt.
Several modifications usually are necessary as the orienta-
tion and focus become clearer. The final version of the
problem statement inthe previous section read as follows:
"The low level of technology on dairy farms
contributes to high costs of production, low
average productivity, and a deficient marketing
system for milk. These factors cause low profits
to the producer, price fluctuations for the con-
sumer, and a deterioration in the balance of pay-
ments because of the necessity to import milk."
Let us assume that we were correct in deciding that
the orientation of the proposal was more toward production
than toward marketing. Let us also accept the relationships
expressed inthe problem statement although many of us may
not be comfortable with some of them. Then, presumably, the
focus of the proposed research project is the low level of
technology on dairy farms, this beingthe cause of the un-
favorable relationships expressed in the problem statement.
Because the hypotheses must be testable within the re-
source limitations, care must be exercised in comparing





resource requirements and limitations before continuing
with the formulation of the proposal. Assume that the client
in this case is the Planning Department of the Ministry of
Agriculture. In preparing their plans for the following
year, they are considering the long range necessity of im-
porting milk. They have'requested a series of studies to
help them clarify the situation so they can make firmer
predictions and to aid them inestablishing domestic poli-
cies. They consider that the country is capable of pro-
ducing more milk but are not sure why it is not doing so.
One factor that is evident is that there is a low level of
technology used in the dairy industry. In this particular
study their desire is to determine why technology has not
improved in recent years, because general knowledge far ex-
ceeds implementation. Professionals will be provided to
work full time on the project, and the Ministry wants a pre-
liminary report in four months and a final report in six.
Generally, calculator and computer facilities are available
and it will be possible to hire the services of some inter-
viewers for a short period of time if necessary.
The first hypothesis might well treat the profitability
of the new technology because, if it is not profitable, most
assuredly the producers will not adopt it. For a beginning,
let us use:
1) "There exist in the country improved methods
of dairy production which, if used by pro-
ducers, would increase their profits."
Stated in this fashion the hypothesis does indicate
the possible direction which the research might take. In
verifying or rejecting it, one method might be a simple re-
view of literatureto determine if we can satisfy ourselves
as to the existence of profitable new technologies. Per-
haps the technologies which are available have never been
subjected to tests of profitability, which would indicate
the need for some partial budgeting or possibly linear pro-
gramming for series of typical farm resource situations.
Of course it might also be true that the client is satis-
fied that there are profitable new technologies and there-




fore does not desire or require verification of this hypo-
thesis. Assuming that we will need to include this hypo-
thesis in the project, further classification will be made
in the statement of the objectives and the procedures.
The hypothesis can be stated in an if-then form, "If
farmers adopt presently known technology then their prof-
its will increase," and the relationship to the problem
statement is clear. Hence, it satisfies the first requisite
of hypotheses.
Depending on the other hypotheses which are derived,
all of the previously discussed means of verification or
rejection of the hypothesis could be accomplished under the
limitations of the budget which we have described.
The theoretical implications of the hypothesis are
about as simple !as it is possible to make them and still
retain meaningful relationships to the problem. To be prof-
itable, the new technologies must fit within the resource
restrictions of the farmer and must be profitable given
present or projected price situations. Notice that it is
not adequate, even though it is simpler, to hypothesize
only that the new technologies could increase farmers' pro-
duction.
The last criterion of hypotheses applies to all of
them taken together, so it cannot be applied individually
except inmthe sense that it would not be adequate to consider
only an increase introduction without considering, at the
same time, the profitability of the practice.
Assuming that in-the course of the research we will be
able to accept the first hypothesis, we must then consider
additional hypotheses because the first, alone, is not ade-
quate to answer the question put to us by the client. The
second hypothesis might be that,
2) "Farmers are not aware of the new technologies."
As stated this is known fact, but the if-then implication
is that if farmers are not aware of profitable alternatives
then they will not (or cannot) adopt them. The direction
of the research in this case is also indicated. A sample





survey of farmers should be able to provide the evidence
necessary to accept or reject the hypothesis.
Another hypothesis could treat credit, orthe related
financial situation of the farmers.
3) "If special credit sources are not made
available, farmers will not be able to
adopt the new technologies."
This can be considered a broad hypothesis with two sub-
hypotheses which will be tested,
a) "Farmers are unable to adopt new technologies
because internal financial resources are lim-
ited."


and
b) "Farmers are unable to obtain credit, which
limits their ability to finance changes in
their production techniques."
An additional hypothesis could treat the problem of
price instability from the point of view of the producer.
4) "A milk price stabilization program could induce
farmers to adopt improved methods of production'."
This hypothesis is not quite as straightforward as the others.
To be able to verify or reject it empirically, a great deal
of time and money would be involved -- certainly more of
both than we have available within our research budget.
However, attitudes of farmers toward price program could
be ascertained and certain conclusions drawn regarding the
probable outcome of such a program. Again, if this hypo-
thesis is included, the precise nature of the research pro-
cess will need to be specified in the objectives and the
procedures.
Other possible hypotheses could be suggested, but those
proposed above are adequate for present purposes. Probably,
all can be accomplished within the research budget, but it
will be necessary to clarify them further (and perhaps mod-
ify them) as we develop our statement of objectives and pro-
cedures.
In summary, our hypotheses are the following:
1) "There exist in the country improved methods
of dairy production which, if used by the
producers, would increase their profits.





2) Farmers have not adopted the new methods be-
cause they are unaware of their existence.
3) Special credit sources are necessary if dairy
farmers are to adopt improved methods of milk
production.
a) Dairy farmers are unable to adopt new
technologies due to internal financial
resource limitations.
b) Dairy farmers are unable to obtain credit,
which limits their ability to finance
changes in production methods.
4) A milk price stabilization program could induce
farmers to adopt improved methods of produc-
tion."
Are these hypotheses, taken together, adequate and
efficient in suggesting a means to one or more meaningful
solutions to the problem? If they cover the range of pos-
sibilities open to the government (extension programs, cred-
it programs, and/or price programs, for example) they should
be adequate in suggesting guidelines to one or more meaning-
ful solutions. They are efficient if we cannot contrive
other hypotheses which could provide solutions to the prob-
lem with the use of fewer of our research resources, do so
in less time, or result inmore precise information within
the research budget.


Delineation of the Objectives


Objectives usually are. expressed in lay terminology
and are directed as much to the client as to the researcher.
The primary objective of applied research will be either
1) to'suggest or recommendtothe client practical means
of problem resolution, or 2) to provide information to
clarify an unknown situation. Generally, the objectives
taken as a group will 1) define the limits of the research
project for the researcher, 2) clarify the means of con-
ducting the research, 3) identify the client or clients,
and 4) describe the expected product of the research for
the client.
The objectives link the theoretical relationships pre-
sented in the hypotheses to the analytical and methodolgical





orientation necessary for conducting the research. An ob-
jective specifies what the researcher intends to do or find
in the project and suggests one or more research procedures
to be used. Later in the research proposal the specific pro-
cedures must be defined. These procedures of course, must
be appropriate, not only to the stated objectives but also
to the resource availability as discussed in Chapter II.
It is necessary, therefore, that the objectives be suffi--
ciently broad to satisfy the needs of the client but also
sufficiently specific to conform to budgetary restrictions.
An erroneous idea of the nature of the objectives of
a research project should be clarified. Research objectives
are neither political objectives nor are they objectives of
an action program of the government. Objectives of a re-
search project suggest what information will be obtained
for the client to help resolve the problem which initiated
the research. This information, in turn, can be used by
the client to establish an action program. For example,
"to redistribute land in Mexico" suggests a government ac-
tion program.This cannot be an objective of a research proj-
ect. But, "to study the past and present agrarian reform
programs in Mexico and their effects on land redistribution"
is a legitimate research objective related to a felt need
concerning land use and productivity. In the terms of our
dairy problem, "to establish a credit program for dairy
farmers" is not a legitimate research objective, though it
may be feasible solution in the mind of the researcher and
the client. "To determine if dairy farmers are able to ob-
tain credit for improving methods of production," or "to
recommend methods of resolving credit deficiencies if iden-
tified," on the other hand, are acceptable research objec--
tives.
Given these conditions, the primary objective of the
dairy study which we are proposing could be, "to determine
the obstacles to the adoption and optimal use of new tech-
nology by dairy farmers." This objective precisely describes
the purposesof the project. Accomplishing this objective





will provide information to clarify an unknown situation
for the client, and, if we are successful, should provide
him with the information he needs tomake policy decisions
and predictions concerning future milk supplies.
Secondary objectives can include the following, listed
in order of their relationship to the hypotheses:
1) Determine if presently known modern technology
is profitable to the dairy farmers given their
present resource situation and market outlet.
2) Determine if the Extension Service is effec-
tively providing necessary information to
farmers concerning possible alternatives for
production.
3) Determine if the required changes to adopt
new technologies on farms are outside the
financial means of the farmers.
4) Ascertain whether present credit sources are
adequate in providing for the farmers' needs
related to new practices.
5) Obtain farmers' opinion about a price sta-
bilization program and their possible reaction
to it with respect to changes in use of tech-
nology and concurrent production practices.
Notice that each of these objectives is directly related
to hypothesis and help to clarify the direction of the re.-
search. If the client does not understand the terminology
used in the hypotheses, he should be able to understand the
nature of the research from reading the objectives. Also,
the objectives clarify the means of conducting the research.
It is clear that interviews with dairy farmers willbe ne-
cessary and, in general, what the content of these inter-
views will be. Specific questions must be written from the
guidelines given in the objectives. These questions either
singly or as groups will provide the information to test
the hypotheses.
Of special interest is the fifth objective. The re-
lated hypothesis (a milkprice stabilization program could
induce farmers to adopt improved methods of production)-states
a positive relationship without giving any indication of the
nature of the test which the researcher has in mind. The
client in such a case could well formulate an erroneous im-
pression of the nature of the results which the researcher





proposes to present him. The fifth objective specifically
states that the researcher expects no more than to obtain
the farmers' opinions and possible reactions. This is
clearly different from empirical evidence which the client
might otherwise expect if he only had the hypothesis for
information.
We have been talking about a special or explicit client
but other clientele could also benefit from the research
in question. If the researcher is hired specifically by a
client, and the client considers the researchprivate,then,
of course, he is the only one who will directly benefit from
the work. However, as is more often the case, this type of
research is undertaken byapublic or semi-public entity so
the research becomes public property and the identification
of a broader audience is useful. In the context of the pres-
sent problem, the full clientele could be identified ina
sixth objective:
6) Provide information to farmers about the
profitability of new methods of produc-
tion, to bankers and other credit insti-
tutions of possible sources of new busi-
ness, and to government planners to aid
them in making decisions concerning the
future of the dairy industry.


Summary


Three of the most important and critical aspectsof the
planning of a research proposal --problems,hypotheses,and
objectives -- have been presented and discussed. These three
parts are not independent from each other, nor are they in-
dependent from other portions of the proposal and aspects of
conducting the research to be discussed in following chapters.
They serve as a framework for developing the data collection
and analytical procedures, the budget including time sequen-
ces and the publication plans for the research results.
Time spent in careful development of the problem state-
ment, the hyptheses, and the objectives is the key to effi-
cient research and can well be the most productive use of





time by the researcher. Even in cases where the researcher
may have only one month, one week, or perhaps just one day
to provide an answer, the time spent in this phase of the
research is critical to the success of the undertaking. On
many occasions whenaperson is givenarush task, the ten-
dency is to "come up with something." Little time is devoted
to analyzing the situation to determine precisely what the
client wants, what is really needed, and what resources are
available to accomplish the necessary task. Too often the
results have no value because the "something"which the re-
searcher "comes up with" is not really related to the problem
of the client.
Problems appropriately specified for applied research
have the following characteristics:
1) They are based on felt needs of individuals,
groups, and societies;
2) The causal relationships expressed in aprob-
lem statement are not hypothetical and are
relevant to the problem;
3) Problem statements must suggest testable hy-
pothetical relationships that, when analyzed,
yield relevant and non-trivial results;
4) The problem and the research to resolve the
problem must be relevant and manageable with
resource restrictions.
Researchable problems can be distinguished from problematic
situations in that numerous researchable problems can be
formulated from a problematic situation.
The hypotheses serve as guides to executing the re-
search. Hypotheses must:
1) Be stated to provide direction for the re-
search.
2) Be formulated as causal relationships with
i--then implications;
3) Be capable of tests within the limits of the
research resources;and
4) Be stated as simply as possible; and
5) As a group be adequate and efficient in
suggesting means to one or more meaningful
solutions to the problem.





Objectives in general describe what is expected to be
achieved by the project. Specifically, objectives:
1) Define the limits of the research project;
2) Suggest or clarify the means of conducting
research;
3) Describe the nature of the potential research
product to the client; and
4) Identify the client or clients.
The following problem statement, hypotheses and objec-
tives are those of the example discussed in the chapter.


Problem:


The low level of technology on dairy farms contributes to
high costs of production, low average productivity, and a
deficient marketing system for milk. These factors cause
low profits to the producer, price fluctuations for the con-
sumer, and a deterioration in the balance of payments because
of the necessity to import milk.


Hypotheses:


1. There exist in the country improved methods of dairy
production which, if used by the producers, would increase
their profits.
2. Farmers have not adopted new methods because they are
unaware of their existence.
3. Special credit sources are necessary if farmers are to
adopt improved methods of production.
a. Farmers are unable to adopt new technologies
due to internal financial resource Limitations.
b. Farmers are unable to obtain credit, which
limits their ability to finance changes in pro-
duction methods.
4. A milk price stabilization program could induce farmers
to adopt improved methods of production.


See the appendix for an example of a complete project
statement.





Objectives:


1. To determine the obstacles to the adoption of new tech-
nology by dairy farmers.
2. Determine if presently known modern technology is pro-
fitable to the dairy farmers given their present resource
situation and market outlook.
3. Determine if the Extension Service is effectively pro-
viding necessary information to farmers concerning possible
alternatives for production.
4. Determine if the required changes to adopt new techno-
logies on farms are outside the financial means of the
farmers.
5. Ascertain whether present credit sources are adequate
in providing for the farmers needs related to new practices.
6. Obtain farmers opinions about a price stabilization pro-
gram and their possible reaction to it with respect to changes
in use of technology and concurrent production.
The chapters to follow will continue with discussions
of data sources and collection, and analysis and presenta-
tion of research results, all of which depend upon well
specified problem statements, hypotheses and objectives.
































PART TWO


CONDUCTING

APPLIED RESEARCH












CHAPTER IV


EXPERIMENTAL DATA COLLECTION


The execution of research involves the collection of
data which pertain to the project, the utilization of the
data to test the hypotheses (usually called analysis of the
data), reaching conclusions which are useful in the reso-
lution of the problem which initiated the research, and mak-
ing appropriate recommendations to the client. If the pro-
ject has been properly planned, the type of datawhich are
needed have been determined prior to conducting the research.
The researcher will know if only secondary information will
be used or if primary data collection will be necessary.
The planning phase of the project will also determine if
experimentation is necessary or if the source of data will
be non-experimental. If experimentation is to be used, a
great deal of care must be exercised in experimental design.
Experimentation has been the principle basis for ob-
taining scientific information and will continue, to remain
of paramount importance. The use of non-experimental data,
however, is becomingmore prominent, due to improvements in
measurement techniques and development of more adequate data
series. The advantage of experimental data over non-experi-
mental data is basically the degree of control which the
researcher is able to exert over the variables included in
the study. In most experiments, with the use of the proper
design the researcher can select the factors which will vary,
the levels at which they will be included in the experiment,
and the pattern in which they will be used. By using appro-
priate equipment he can also usually obtain quite accurate
measures of the input variables as well as of the results
of the experiment. With non-experimental data, the levels





and combinations of variables are predetermined by nature
or society, so the researcher must measure and use them as
they exist. Because these variables are very difficult to
identify and measure, non-experimental data are usually
more subject to inaccuracies than are experimental data.


Experimental Design


Experimental design, the form in which the experiment
is to be set up, is a critical factor in the generation of
experimental data.1 There are any number of designs which
can serve a particular need, but there will usually be one
that is better suited to the conditions under which one
experiment is going to be conducted and which is the most
efficient in the use of the research resources. Selection
of the most efficient experimental design will provide more
information directly related to problem resolution for the
given set of research resources than any other alternative
design.
Selection of the number of treatments, the number of
controlled and measured factors, the levels at which the
variables are to be included, and the number of replications
to be used in the experiment is not a simple process. The
final choice.can be complicated in applied research because
the conditions under which the researcher is working are
often poor in relation to what he would like for improved
precision. Good research planning is extremely helpful to
the researcher in choosing an experimental design. This is
so because the design must be related to theproblemand the
methods of analysis to be used and these should have been
carefully considered in the planning phase of the project.







1Selected references on experimental design include
[3,4,7,26].





In the choice of a design, then, the researcher will
be able to anticipate the type of information which willbe
forthcoming from any particular design. He will be able
to predetermine the applicability of the design to the pro-
blem and to the methods of analysis which are appropriate.
The researcher will also ascertain whether or not the ex-
periment can be conducted within his resource limitations.


Relationship to the Problem


Although to achieve measurement "accuracy with exper-
imentation is possible,.it does not necessarily followthat
experimental data as a source of information for research
project will assure research precision. If the design of
the experiment is not properly related to the problem ori-
entation of the project it will not be possible to achieve
precision in determining relationships useful to problem
resolution. An example may best serve to illustrate the
point.
A common type of design in fertilizer experimentation
is the following, with each treatment being replicated a
number of times (frequently four).


Design 1
Variables
Treatment Number N P K

1 0 0 0
2 0 0 1
3 1 0 1
4 2 0 1
5 0 1 1
6 1 1 1
7 2 1 1
8 1 1 0





In the project porposal an objective might read some-
thing like, "to determine the effect of nitrogen (N),phos-
phorus (P) and potassium (K) on the production of pangola
grass in the Cauca Valley." As we now know, of course,part
of the difficulty here is that we do not knowwhat theiden-
tified research problem is. But that aside, the objective
as stated is vague and is not an adequate guide for design-
ing the experiment. Toward what end is the experiment or-
iented? Does the researcher want to know simply,"is there
a response to N, P, and K?" -- or is he more interested in
the magnitude of the response, or even the kind or form of
response over a range of N, P, and K invarioumombinations?
Each of these questions may well require the use of a
different experimental design, number of treatments or
number of replications in order to achieve precision and
efficiency in arriving at an answer. In some cases,two or
more questions can be answered efficiently from one exper-
iment, but in others, the attempt to answer too many ques-
tions from a single design may render the experiment use-
less for answering any question.
Without discussing the theoretical logic for the state-
ments, the following can be said about the relationship of
Design I to some of the questions which could be asked.
When the researcher is interested in knowing only ij there
is a response to each of the three nutrients, it is not
necessary to include all the treatments and levels of N in
the design. A simpler design such as the following could
be used:





Design II

Variables

Treatment Number N P K
1 0 0 0
2 1 0 0
3 0 1 0
4 0 0 1


Here, instead of eight treatments there are only four.
Using four replications of each treatment, only 16 separate
parcels are required rather than 32 as would be necessary
in the first design if four replications were also used.
The choice of the level of each nutrient (1= 100 kg/ha or
1 = 200 kg/ha, etc.) is important because this design pro-
vides information only for the one level chosen.
If the researcher wanted to know the magnitude of the
response for two different positive levels of N, it-would
be necessary to include the three different treatments
(0, 1, 2) of this nutrient. Apparently in the design shown
it was desired to know something about the magnitude of
response to Nfor two different levels of P, because the N
treatments are repeated for 0 and for 1 P. This question
can be answered with the use of treatments 2 through 7 of
Design I.
The last treatment of Design I can only answer two
questions, 1) "Is there an effect from K when N = 1 and
P = 1?" This requires treatments 6 and 8. No other infor-
mation will be available on the effect of K. The last treat-
ment along with the control (treatment 1) can show the
response of N and P together when no K is applied.
Because we are interested in applied research, let's
suppose that the ultimate use of the data from the proposed
experiment will be to make fertilizer recommendations to
farmers. To what extent does Design I permit us to make
the appropriate analyses? One alternative is to compare
the cost and return of each treatment with the control (0-0-0)
and determine the net return from each. Assuming that there





were significant differences between treatments, we could
then recommend the treatment with the highest net return.
Another alternative would be to determine the functional
relationship between N and production (production function
for N) for each of the two levels of P. Assuming the curves
thus generated were of proper form (satisfyingtheconditions
for optimality), we could determine the economic optimum
quantity of N for each level of P, make a cost-return estimate
for each, and choose the one with the higher net return as
that which we would recommend.
The second procedure would probably result in a some-
what different recommendation than the first method. There
is obviously less precisionwith respect to N in the first
method than in the second but theremay be even less precision
with respect to P because we have only two treatments to
choose from. Apparently, the design is not well suited to
answer the question the farmer might ask, "What is the best
combination of N, P, and K to use?" even though it does
appear to be at least reasonably suitable for answering some
other questions.
To answer the farmer's question may require a more
complicated design and could require more resources than
are available, but much more precision is possible if there
are sufficient resources. Asan example, a complete factorial
with 3 or 4 levels of each nutrient would require 27 or 64
parcels respectively for eachreplication but could provide
rather precise answers for the farmer (the use of the 4
factorial, of course, would provide more precision than
would the 33 factorialbut it also requires moreresources).
Another, more efficient design is the rotatable central
composite which is a modifiedfactorial that requires only
15 parcels for each replication when three nutrients are
considered. For this last design, fewer replications are
necessary so that with only about 40 parcels a complete
experiment can be conducted,2 providing a wide range of
information.

2A11 Treatments are not replicated the same number of
times [551.





In summary, the problem toward which the research is
directed has a strong bearing on the type of experimental
design whichshould be chosen if the researcher is going to
use experimentation in the execution of the project. Should
the magnitude of the problem require a very detailed exper-
imental design, the researcher should be encouraged to con-
sult with a competent statistician when one is available.
Also, if the researcher is going to use secondary experimental
data, the design which was used in the experiment should be
considered when choosing between various sources. More will
be said on this aspect in a later section of this chapter.


Relationship to Resources


The ultimate size and complexity of an experiment de-
pends on many factors including number of independent factors
to be controlled or measured, analytical techniques to be
used, statistical precision required, quantity and quality
of prior information available, the objectives of the re-
search project, the time within which results must be ob-
tained, and the resource constraints encompassing the re-
search project.
If it is necessary to determine the best combination
of N, P, and K, a rather complex design with a relatively
large number of experimental observations (parcels) is re-
quired. But if it is simply not possible to conduct such
a complex experiment, the research project must be modified.
For example, if some information-is available which indicates
little or no response to K, then the number of independent
variables could be reduced to two (N and P) and K could be
excluded or held constant at some predetermined level in
the experiment. The best combination of N and P can then
be determined with a rotatable central composite design
requiring only about 26 experimentalunits rather than the
40 units required for three independent factors (N, P, and
K).





The design can be simplified further by considering
only one independent factor. This factor could be the one
considered most important such as perhaps N or it could be
some fixed combination of several factors such as a complete
fertilizer containing N, P, and K with an analysis of 10-
30-10, for example.
An experiment requiring only about 15 experimental units
will yield as much statistical precision for one factor as
26. for two factors. But it is important to realize that the
total amount of information is reduced accordingly as the
number of independent factors and resource requirements are
reduced. With three factors and 40 parcels, we should be
able to tell the farmer, who is on similar soil as that used
for the experiment, howmuch N, how much P, and how much K
he should use to achieve the greatest net returns from fer-
tilizer use. With two independent or variable factors, we
have the option of telling the farmer the best combination
of only two nutrients and can do that only for some pre-
determined quantity of the third nutrient. With only one
variable factor it is not possible to recommend best com-
binations but only the best quantity of that single factor.
We maybe able to recommend300 kilos per hectare of 10-30-10
as the best quantity of that complete fertilizer, but we
would not be at all confident that the resulting 30 kilos
of N, 90 of P, and30 of K would be the best'combinationof
the three nutrients to use.
The effect on resource requirements of the analytical
technique to be used is more complex, but an example will
serve to illustrate the point. Suppose that it is desired
to determine if there are significant differences in the
response of three different levels of new feed additive on
fattening steers. Aprobable design would have three treat-
ments with the additive (one for each level to be tested)
and a control. This results in four treatments per repli-
cation. Under most conditions three to four replications
have been found to be required to obtain reliable statistical





estimates and provide enough degrees of freedom for this type
experiment and the analysis of variance which would be used.
A total of 12 to 16 experimental units (pens of cattle) would
be required to execute the research.
An alternative to analysis of variance is regression
analysis. If this technique is envisioned for the feed
additive experiment the same four treatments could be used
and if the interval between treatments was not uniform,
they could be adjusted to make them equal (a desirable though
not necessary attribute of a design for regression analysis).
In analysis of variance, the observations from only two treat-
ments are compared at anyone time. In regressionalanalysis
the observations from all the treatments are considered sim-
ultaneously. For this reason roughly the same amount of
statistical precision can be obtainedwith two replications
of the four treatments for regression analysis as with four
replications of the four treatments for analysis of variance:.
Hence, regression analysis may require fewer experimental
resources than analysis of variance. Similar relationships
hold for other types of analysis which may be required in
the project and should be considered when choosing the design
to be used.
The statistical precision required in experimental
results is associated closely with the nature of the problem
for which the research is being undertaken. Lower levels of
confidence are acceptable in research dealing with animal
health than with human health, for example, and lower con-
fidence levels may be satisfactoryin some social research
than in some biological research. But regardless of the
nature of the research, an increase in the precision required
is almost always associated with the need for more exper-
imental resources. For any givenresearch objective or exper-
imental design, more replications and/or more treatments will
usually result in more precise statistical estimates than
would fewer treatments or replications.
In addition to increasing the number of treatments or





replications, precision can also be increased by closer super-
vision and better control during the experimental process.
Spotty application of fertilizer by hand broadcasting on
grass plots can result in large experimental errors as can
carelessness and lack of thoroughness during harvest. More
time, workers with more skill, or specialized machines or
equipment can reduce this source of experimental error, but
all will add to the requirements for experimental resources.
From a practical point of view, the least expensive means
of reducing experimental error from this source is closer
supervision by the researcher during all phases of the exper-
imental process. Time spent at the experimental site by the
researcher can be highly productive particularly when it is
possible to prevent the complete loss of data through care-
lessness.
The use of prior information can reduce the need for
resources by reducing the range and number of treatments
otherwise required, by taking advantage of known estimates
of variance to minimize the number of replications, and
perhaps even by providing all the data needed making further
experimentation unnecessary. In the following section we
will discuss in more'detail the use and utility of secondary
experimental data, whichis one sourceof prior information
available to the researcher.
The time limit within which adecisionmust be made is
also an important factor in determiningthe size and comp-
lexity of an experiment. If time is not a critical factor,
an exploratory experiment of relatively simple design can
be conducted and this can be followed by an experiment which
is more exact in its focus. The range over which the exper-
iment is conducted can be successively narrowed until the
required accuracy is achieved. None of the experiments in
this sequence need be large nor complex. But if timing is
critical and decisions must be made rapidly, it maybe nec-
essary to increase the size and complexity of the experi-
ment in order to include several links of the chain all at
the same time. That is, to conserve on time (in this case





a very limited resource) other available resources may need
to be substituted in order to achieve usefulresearch pro-
duct within the time periodallowed for making a decision.


Secondary Experimental Data


When experimentation isundertakenin the executionof
the researchproject, the experimental designcan and should
be tailored to the needs of the project. The data obtained
will then be the best available and will be well suited to
the needs of the researcher. But it is not always necessary
to conduct an experiment to have suitable or adaptable exper-
imental data for analysis, because in most places where ap-
plied research is being conducted, at least some prior exper-
imental data are available. These data, though generated
for other research purposes, frequentlyprovide an insight
into the nature of the relationships to be studied in the
current project, and may provide sufficient data so that
additional experimentation need not be undertaken.
In situationswhere time is a limiting factor, the use
of secondary experimental data may be advantageous or even
essential, but data generated by another person or from one
or more other experiments must be usedwith caution to assure
that they are relevant and comparable. Some adjustment or
selection may well be necessary to adapt the data to the
current study.
Several means can be used to adapt, select, or adjust
data of this nature. Onemeans is to select only the rel-
evant portions of the data and exclude those parts not re-
lated to the current analysis. An example would be to select
data in a fertilizer experiment from those parcels where
potash was at a constant level, eliminateplots where trace
elements were included, and make the analysis for the portion
of the data in which only nitrogen and phosphorus were vari-
able.
A second method of using secondary datais to analyze





the results of several experiments and search for congisten-
cies which may indicate relationships not otherwise evident.
In the Cauca Valley, Colombia, production functions for a
series of regional fertilizer trials in corn resulted, indi-
vidually, in very poor statistical estimates. For anyone
trial, little confidence could be placed in the conclusions.
But after dividing the trials into soiltypes, it was noted
that there was a great deal of consistency in the functions
within a soil type. The form of the curves was similar with
each reaching a maximum within a short range, andwith calcu-
lated optimumapplications at about the same levels. Hence,
by using informationfrom all the curves, together, general
recommendations could be made even though the individual ana-
lyses yielded little information.
A third useful method of analysis is to consider the
possibility of combinations of datafrom two or more differ-
ent experiments which were conducted under similar conditions.
This method was used to estimate the optimum stocking rate
for fattening steers on grass from three different experi-
ments E50]. Each experiment was conducted to determine the
effect of hormones, and all were conducted on similar grasses,
under similar conditions and with comparable cattle. Be-
cause the rate of stocking was different in each case, it
was possible to use a mathematical response relationship
from which the optimum stocking rate could be calculated.
One additional point with respect to secondary data
should be mentioned. When one has spent time attempting to
use secondary experimental data, he appreciates the product-
ivity of any efforts made by the first researcher to preserve
the data for other users. Nothing is more frustrating than
to discover a descriptionof an experimentthat should have
provided usable information and then to findthe data in such
poor shape that they are impossible to use. Simple notations
such as units of measurement are often not even included.
The thoughtful researcher will leave a clear record of his
data so that users who follow will have no trouble inter-
preting them.






Multi-purpose Experimentation


As a practical matter, a great deal of experimentation
is carried out with an orientationthat is only partly re-
search centered. An important example in agriculture is the
demonstration trialusually conductedby, or in cooperation
with, the extension service. One of the purposes of this
type of research is to demonstratethe results of research
under realconditions, i.e., under conditions which will be
applied by the client toward whom it is focused. For this
reason rather poor experimental control is to be expected,
and accordingly, the experimental design is nearly always
quite simple. In many cases, as few as two treatments,
with and without a particular input or package of inputs,
are included. At times, complete experiment is conducted
at one location; in other trials, different locations are
considered to be different replications of the same exper-
iment with all treatments being repeated at each; and in
some cases only one or a few treatments are conducted at
each location.
It should be obvious that as more and more locations
are included in a demonstration trial, exposure to the clients
is increased, but experimental control is decreased. Also,
with more treatments in a project, more informationis pos-
sible, but also, the supervision of the project becomes more
difficult. Hence, the persons responsible for the project
must determine,based on the orientationof the project and
the available resources, what the size and scopeshould be.
Presenting an example of a fairly successful demon-
stration trialmay be the best means of discussing some of
the more important aspects to be consideredwhen initiating
a project of this nature. This project was conducted in
southwestern Colombia in an area not far from the city of
Cali. The area comprised that of a large number of descendants
of former slaves who had dividedtheir holding into an average
of about 2 hectares per family. The farms were nearly all





in old stands of cocoa, coffee,and plantain which were in
such poor condition that monthly income per farm barely reached
fifteen dollars. General nutritional deficiency was evident
as was the nearly complete absence of any source of animal
protein. Physical conditions for any type of livestock were
very bad, and, of course, little or no money was available
for supplemental feed.
As part of a development program for this area, it was
thought that Khaki-Campbell ducks (an egg laying breed)could
prove to be a potential source of animalprotein to supple-
ment the diets of these poor rural families. Indesigning
the project, several alternatives were possible. The sim-
plest of those considered reasonable was to select a small
number of families (those most apt to be conscientious in
maintaining the necessary records), to give each about 10
ducks andprovide themwith a recommended concentrate ration.
The results couldprobably be establishedwith a fairlyhigh
level of confidence and would show whether or not the ducks
could survive under the conditions of the area. It would
also be possible to determine the cost of the eggs to the
families and whether or not they would eat the eggs.
A second approach that was considered was to use more
families and experiment with several rations for the ducks.
At first, three rations were considered adequate, with three
families providedwith each ration. In this manner, it was
hoped to be able to determine not only if the ducks would
survive and lay under the severe conditions prevalent in the
project area, but also what the lowest cost ration would be.
In other words, there would be three different rations to
choose from. Although more information could be obtained,
more families would be needed and more supervision required
to assure that the rations were correctly administered. The
extension personnel who were cooperating in the project felt
they could find nine families and had sufficient resources
to do the majority of the supervision. Over 100 young female
ducks were going to be available, so the extension people





began to locate the cooperating families.
As it turned out, 16 familieswere eager to cooperate
in the project, and the extension people felt this number
should not be too great a supervisory burden. The use of
this many families would reduce the number of ducks available
per family to seven. It was decided that this wouldbe sat-
isfactory, but that it would be more efficient in the use of
the families to include four rations and have four replications
of each. With four rations it was hoped that there would be
sufficient information to estimate a production function for
eggs andwith this information be able to determine the lowest
cost ration even if it were not one included in the experiment.
The final design included one group with a complete con-
centrate ration, one with 2/3 of this amount, onewith 1/3of
a ration, and a control group with no concentrate. Except
for those receiving a full ration, all could receive what-
ever scraps were available and be allowed to graze (or be
fed chopped grass). Material for constructing adequate
housing for the ducks was available locally at no cost and
all families were required to be ready to receive the ducks
by a fixed date.
A one day short course was held with all families par-
ticipating sufficiently far enough in advance of the delivery
date to allow time for construction of the housing. The
care of the ducks was discussed and also the design of the
experiment and its purpose. The families were all given
very simple record forms and instructed in their use (to
be able to use the forms it was not necessary to be able to
read or write or even count). Cups were provided to measure
the exact amount of feed for each duck for each ration so
that in the event of losses, the adjustment of the ration
would be simple. At the close of the course a meal including
duck eggs was served to assure the families that the eggs
were good to eat since there was some local bias against
eating the duck eggs.
With the encouragementof the extension agent, all par-





ticipating families were ready on the date that the twelve
week old ducks were delivered. Initially, extension field
men and the researchers checked frequently with the families
to ascertain if everything was being done properly. The
records were collected every two weeks during the whole pro-
ject to assure they were kept current.
To be sure, there were rather large differences in the
results for each ration. One family, for example, never was
rewarded with even one egg. Although they were a bit embar-
rassed and the neighbors were sure they were not taking good
care of their ducks, they took it good naturedly because they
were assured that this was not unexpected and was a necessary
part of the experiment. Nevertheless, by having four repli-
cations and using the average for each ration, adequate in-
formation was obtained. It was possible to determine the
best level of concentrate to use if the eggs were going to
be sold, as well as the rationwhich resulted in the lowest
cost for the eggs if they were to be used to supplement
the family diet. The second use, of course, was the primary
purpose of the project.
Upon completing the analysis of the results, a field
day was held for the families at which time the results
were presented. After the general results were shown,those
of each family were discussed in an attempt to determine why
some had better results (hence lower costs) than others with
the same ration. Following this discussion, all the families
participated in the selection of the final recommendations
which were published [55].
In summary, this project was tailored to fit within the
,resources available and yet to provide the greatest exposure
in the project area. Although experimental controlwas re-
latively low, sufficient treatments and replications were
included to maintain adequate statistical reliability inpart
due to the presence of a high degree of supervision by the
researchers.
Multidisciplinary experimentation is another means of




conserving scarce research resources. Whenresearchers from
two or more disciplines cooperate in a project it is fre-
quently possible to obtain answers for each with little change
in the basic experimental design.3 Too often a researcher
in one discipline minimizes the effects of those factors com-
monly included by others, so that in the absence of cooper-
ation, the product is of low value to other researchers. An
example occurs in beef or dairy projects where the researchers
raise their own corn for silage without the cooperation of the
corn researchers who may be at the same experiment station.
The animal researchers may be able to document accurately
the effect of the silage on the animals but be unable to
estimate animal production perhectareof corn because they
had little interest in the corn production. Even more dif-
ficulties will arise if it is later desired to make an econ-
omic evaluation of feeding silage to animals [46].
Of course, it is not always possible to obtain answers
for more than one discipline without increasing the size
and the complexity of the experiment beyond manageability
and available resources. But it is precisely in those cases
when resources are most scarce that it is important to con-
sider the advantages of multidisciplinary research. Most
experiments are costly both in terms of time and of other
resources so it is obvious that if the results can serve
two or three researchers, the additional effort required in
planning the experiment can be extremely valuable [60].


Summary

Experimentation and experimental design usually are
associated with objectivity, precision, and scientific purity
-- concepts that imply rigidity and inflexibility in thought


3For a brief and excellent discussion of multidisci-
plinary cooperation in extending experimental results to
practice see [67].





and procedure. In basic research this is mostly true, but
in applied research, considerations other than pure scienti-
fic objectivity can become more important in determining the
type of design to be used for any given experiment. Resource
limitations will usually force a reduction in the accuracy
obtainable, and factors such as demonstration uses will
modify the nature of the design ultimately selected. It is
important that the applied researcher maintain a flexible
attitude with respect to experimentation and experimental
design in order to increase his effectiveness and make him
more efficient in his work.









CHAPTER V


NON-EXPERIMENTAL DATA COLLECTION


A major difference between experimental and non-experi-
mental research is the degree of control the researcher ex-
ercises over the variables being studied or measured. In
an experiment, the researcher controls the design and levels
of certain variables and the measurement of phenomena re-
sulting from the experiment. In non-experimental research,
the researcher in most instances cannot determine the design
and level of the variables nor directly measure the pheno-
mena, but controls only the technique used in measurement
(primarily a sample survey and questionnaire). For non-
experimental observations sample survey design plays a role
comparable to that of experimental design when experiments
provide the observations to be analyzed. Again, a compe-
tent statistician, if available, can be a helpful consul-
tant.
The non-experimental researcher relies upon interviews
and questionnaires to communicate his measurement need to a
respondent. Often it is the respondent, not the interviewer,
who performs the measurement based upon his experience. The
respondent's experience may be compiled, for example, in
farm records or consumer budgets, but frequently his respon-
ses are based upon a subjective evaluationof the phenomenon
as he best remembers it.
Thus, in non-experimental research the researcher usu-
ally controls only the general levels of variables, through
stratification and sample selection of respondents, ques-
tionnaire development and interview training. Successful
non-experimental measurement rests primarily upon all uf
these activities. But even with a good sample, a tested
questionnaire, and a well trained interviewer, the re-





searcher cannot completely control interviewer-respondent
communication, part of which may be misleading [16].
This chapter will first focus on the selection of re-
spondents and the design and implementation of questionnaires
and then discuss verification and preparation of both primary
and secondary data for analysis. No specific emphasis is
given to unstructured interviews and case studies because
most of the approaches included are applicable in these si-
tuations. Time and resource restrictions along with the
needs expressed by the hypotheses and objectives will dictate
whether the measurement process will be a large survey or a
case study [31].


Selecting Respondents


The selection of the respondents, or sample design, is
an extremely important part of the process of non-experimental
data collection. Because the researcher has no control over
the distribution of the factors he is studying (these exist
as result of nature and social organization), the proper
selection of the respondents is necessary to assure that the
information is being obtained from an appropriate population.
Once respondents have been selected and the interview process
is completed, a faulty or ill-designed sampling procedure
may generate data that do not describe the target population.
To resolve'this difficulty more time and resources, if avail-
able, must be expended than would have been necessary with a
more carefully designed sample.
Two commonly employed sampling approaches are the ran-
dom sample and the stratified sample [8,18,20]. For infor-
mation of a broad census nature, a completely random sample
gives each person in the total population (all farmers, high
school students, married women, etc.) an equal chance of
being chosen. In this manner, results can be associated
with the characteristics of that population. Stratified
samples where particular sub-groups are chosen are used to
assure that each sub-group is equally represented, or to
assure uniformity or representation over specific ranges of





certain group traits (different farm size or different in-
come groups for example). Such a stratified sample can ap-
proximate experimental measurement but with less precision
than is normally associated with experimental research. A
stratified sample is often more efficient than a random sam-
ple in use of scarce research resources because the sample
size required may be samller thus reducing both interview
and data processing expenses.
In drawing a sample, one hopes to have available a
reasonably good listing of the general population including
some descriptive characteristics to aid in stratification.
To help determine the sample size measures of variance within
the population may then be calculated and used along with re-
source limitations and levels of confidence desired by the
researcher and his client.
Many times in applied research, these general charac-
teristics of the population are unknown, making sample se-
lection more difficult. One researcher studying farms in
a jungle area was forced to utilize somewhat unorthodox but
otherwise relatively functional techniques [42]. In one of
the three zones of the region to be studied maps were avail-
able showing farm locations. A simple random sample of
farms was easily obtained from these maps. In another zone
"trail maps" were available but the farms were not included.
The approximate number of farms in total was known and the
trails and farms were, in general, uniformly distributed
throughout the region. A complete enumeration to develop
the sample frame would have been difficult and would have
required more time than was available. The researcher chose
to send out interviewers by mule with instructions to ob-
tain an interview at every fifth farm. The sampling problem
was thus handled as the interviews were taken. In the third
zone, maps were extremely poor and little was available to
guide the sampling process. To assure that the entire zone
would be represented, the interviewers were instructed to
ride their mules for one hour and then taken an interview
at the nearest farm, again proceeding along the trail. As
one might expect, errors did result, but adjustments in the





analysis were based upon general observations made by the
researcher while in the zone.
Had logistical problems not been so extreme, the above
researcher could have used a sequential sampling technique.
That is, based upon predetermined level of confidence, he
could have measured the variance in selected population char-
acteristics by using the interivew data taken daily While in
the field. From this calculation he could then determine
when the sample had reached the size needed by reducing the
variance to meet the desired confidence level. When that
level had been achieved he could have moved to another zone.
A further need for flexibility in the sampling process
to allow for obtaining needed information is illustrated by
a research project recently completed in the East Uttar
Pradesh of India [58]. Initial interview attempts with
Indian farmers concerning their landholdings were met with
considerable suspicion and apprehension, possibly, because
of speculation about land ceiling legislation. Interviews
conducted in villages as planned encountered farmers un-
willing to.provide the desired information. Yet when the
farmers were selected at random while traveling along the
roads in the district they responded readily to questions
about village and other matters related to land owernship.
Since personal identity and specific location of the re-
spondents were not imperative the sampling approach was
changed substantially but to the benefit of the entire re-
search effort.
In summary, a flexible researcher who places major em-
phasis on problems and views his sampling techniques as tools
and not ends in themselves will be able to perform applied
non-experimental research under much less than optimum con-
ditions.


Designing the Questionnaire


At the risk of seeming elementary, it is advisable to
emphasize that questionnaire development must be closely




tied to the problem, hypotheses, objectives, analytical tech-
niques, and available resources for the proposed research.
Just as the research proposal orplan must reflect a rele-
vant problem, and the hypotheses and objectives must pertain
directly thereto, the respondents to be interviewed and the
questions to be asked must be relevant to the research pro-
posal. Beyond relevancy, a questionnaire must include only
those questions that are highest in priority for analysis
and testing. A multitude of questions could be "relevant"
or "interesting" but only a limited number can be used fully
in the project because of research resource limitations.
Interview time, for example, represents a costly resource
allocation not only for the research project, but also for
the respondent. The researcher must always remember that
excessive and/or irrelevant questions try the respondent's
patience, reduce interviewer-respondent rapport, threaten
credibility of the responses, and waste scarce resources of
the research project.


Difficulties in Interpretation and Communication


The method of obtaining information in a questionnaire
is the'spoken.word, so language problems must be given special
consideration. Obvious problems arise when questions are
translated from one language to another, but even within
the same language, word and expression usage vary with dif-
ferent cultural, social, educational, and economic classes.
Differences of interpretation may exist between the research-
er and the interviewer as well as between the interviewer
and the respondent. There will also be differences be-
tween respondents in the interpretation of some questions.
The magnitude of this difference will increase as the het-
erogeneity of the sample increases.
The complete elimination of language problems is nearly
impossible, but careful consideration of cross-cultural com-
munication difficulties will minimize problems of interpre-
tation in the questionnaire. Two major cross-cultural commu-





nication problems in questionnaire formulation are differen-
ces in terminology and cultural differences in beliefs and
values.
The names by which things are known or the terms which
are used to describe something vary widely even within a
language and culture group [17]. These differences in ter-
minology must be considered in the construction of the ques-
tions. Generally, the lower the general level of education
and the greater the degree of isolation, the more important
it is to take local usage into account. When groups are iso-
lated, indigenous objects and phenomena frequently have names
which are known only within the groups. Objects or phenomena
which are not indigenous will probably have similar names,
but if they are unknown within the group, they may be diffi-
cult to explain. Terms used by professionals maynotbe under-
stood at all by the respondent, yet if the interviewers are
allowed freedom in explaining these unknown terms, an in-
terpretational bias may arise. In some cases,professionals
may be able to communicate with each other and with the in-
terviewers with one question, but several questions maybe
necessary to obtain the information from the respondents of
a survey.
A common example of varied usage in Colombia is the
problem with land measures. Four measures, the hectate,
the plaza, the cuadra, and the fanegada, are used in dif-
ferent parts of the country. When a survey is conducted,
one must construct the questionnaire to account for this
variation of risk interpretational errors in measuring farm
size, crop yields, and other factors associated with land
area.
A different problem arose in Colombia with respect to
a question concerning tapeworms in swine. In each of three
different departments (states), different local term had
to be used in the question to avoid erroneous conclusions


1The question is from a questionnaire which provided
information for a Masters thesis [49].




whichcould have been drawn when determining the respondents'
knowledge of the incidence of this parasite in the survey
area.
Unknown or misunderstood differences in beliefs and
values are the other important cause of interpretational prob-
lems. An example can be drawn from interviews with house-
wives in a Colombian village where the drinking water was
badly contaminated [27]. Many of these housewives realized
the importance of boiling their drinking water and under-
stood the technique involved but still did not do it. In-
formal interviews determined how many housewives did boil
water, how many realized they should, and how many understood
the technique, but the survey failed to determine why the
majority did not actually boil water.The difficulty. developed
because appropriate questions were not asked due to inadequate
cultural knowledge. The professionals assumed that. boiling
water was "good", and based upon survey results and their
own normative considerations, they determined the housewives
"should" have been boiling water. Only after further ques-
tioning did the researcher discover that the villagers be-
lieved that water was boiled only for the very ill. Those
who drank boiled water were considered to be ill, so to avoid
this stigma, many who otherwise might have boiled their water
failed to do so.


Designing for Data Retrieval


A questionnaire must lend itself to efficient and use-
ful data collection, processing and analysis. The allocation
of time and resources between fieldcollection and data re-
trieval and verification from completed questionnaires needs
careful consideration when designing a questionnaire. Long
and detailed qualitative responses to open-ended questions
may be more informative than quick semi-quantitative responses
involving selection of alternatives, but the time required
to correctly obtain, retrieve and analyze one long response
may be the same as for twenty short selective response ques-
tions. One must determine which of these two techniques (or





combinations of both) most efficiently provide information
while minimizing interpretation and response errors.
Both collection and verification are facilitated by
logic and consistency and by organizing the questions to
lead the respondent with ease through the questionnaire in
a manner that stimulates spontaneity inhis responses. If
one question asks about his marketing problems for rice, and
is followed by the age of each member of his family, and the
next returns to the price of rice, the interview becomes
burdensome and less effective. One exception to this rule
is important. If one desires to cross-check or verify a
particular response because of interpretational problems or
a reluctance to respond accurately, it may be desirable to
ask the same question twice, each time in a different manner
and at different points in the interview.
Dividing the questions into major groups will help re-
duce respondent fatigue while maintaining interest. Groups
of questions that involve sensitive issues;such as income
or profit that may be subject to taxes, might follow several
relatively less sensitive groups of questions in order to
establish rapport and confidence. Sensitive issues covered
prematurely in.a questionnaire may destroy the entire inter-
view and thus should be asked toward the close of the inter-
view.
Coding, or preparing the data for computer analysis, is
necessary if the data are to be punched oncards for elec-
tronic data processing. Precoding which refers to specifying
on the questionnaire the column requirements for computer
cards, can eliminate the need to transfer the data to code
sheets by permitting the data cards to be punched directly
from the questionnaire. This method requires more careful
editing of the questionnaire but usually reduces retrieval
costs and the chance of human error by removing one transfer
of data. To be more efficient, however, the researcher must
be certain beforehand of how he wants to organize and process
the data. The editing and checking process, on the other
hand, helps assure that all necessary data will evolve from




the questionnaire. Precoding is less advisable for highly
qualitative responses or when the researcher has no indica-
tion of the range of responses he might expect for each
question.


Pretesting the Questionnaire


Pretesting the questionnaire or checking to see if it
will obtain the information sought, must be accomplished un-
der actual field conditions before beginning the general
survey. No amount of intellectual exercise in the office
can substitute for properly testing a questionnaire among
the respondents in the area to be surveyed. This phase will
determine the weaknesses in the questionnaire, establish
whether the information sought can be obtained in a useful
form, and also may provide additional information which can
help improve the relevancy of the questionnaire.
Whenever possible, the interviewers who will be conduc-
ting the survey and the director of the research project
should be involved in the pretest to assess problems with
the questionnaire and with respondents. Prior to protesting,
interviewers should become familiar with the research project
and the questionnaire. Each interviewer should be carefully
briefed and sent to several of the different areas which have
been selected to assure experience with a variety of respon-
dent types. When each interviewer returns, a debriefing with
the researcher should be performed immediately.This debrief-
ing should include review of the completed questionnaire
to identify points of misunderstanding, unnecessary repeti-
tion, time difficulties and so on. General reactions by
both the respondents and the interviewers concerning the
subject matter and length of the questionnaire should be
discussed.
For some interviews care should be taken in selecting
the areas where the pretest will be performed to avoid the
danger of contaminating major target area by pre-testing
the questionnaire within its bounds. Especially in close-





knit rural areas, advance knowledge of attitudinal responses
in the final survey could be affected by word of mouth dis-
cussion among potential respondents and those participating
in the pretest.


Size of Pretest


The required number of pretest questionnaires depends
upon the research problem, the homogeniety of the survey
population, the data collection and analytical techniques
to be employed, the total number and complexity of the
questions tobeasked, andtheresearch resources available
fortheproject. The range may be from five to one-hundred
or more questionnaires. If the population is very hetero-
geneous with respect to information required, more inter-
views willbenecessary for an adequate pretest than fora
questionnaire to be administeredtoa more homogeneous popu-
lation.
If the pretest is also to provide desired information
about variance to determine the population homogeneity for
sampling purposes, more pretest interviews may be needed
than when only a test of the questionnaire is desired.For po-
tentially large studies where general population parameters
are unavailable, a rather extensive pretest can aid in de-
signing the sample. The marginal costs associated with
these additional pretest questionnaires must be measured
against costs associated with sampling errors due to having
too few respondents. Extra costs resulting from obtaining
excessive questionnaires in the main interview effort may
be greater than the costs for a few additional questionnaires
in the pretest.


Information Checking


How a pretest improved a particular question ina sur-
vey of settlers in the colonization project in Caqueta,
Colombia is illustrated as follows [48].





knit rural areas, advance knowledge of attitudinal responses
in the final survey could be affected by word of mouth dis-
cussion among potential respondents and those participating
in the pretest.


Size of Pretest


The required number of pretest questionnaires depends
upon the research problem, the homogeniety of the survey
population, the data collection and analytical techniques
to be employed, the total number and complexity of the
questions tobeasked, andtheresearch resources available
fortheproject. The range may be from five to one-hundred
or more questionnaires. If the population is very hetero-
geneous with respect to information required, more inter-
views willbenecessary for an adequate pretest than fora
questionnaire to be administeredtoa more homogeneous popu-
lation.
If the pretest is also to provide desired information
about variance to determine the population homogeneity for
sampling purposes, more pretest interviews may be needed
than when only a test of the questionnaire is desired.For po-
tentially large studies where general population parameters
are unavailable, a rather extensive pretest can aid in de-
signing the sample. The marginal costs associated with
these additional pretest questionnaires must be measured
against costs associated with sampling errors due to having
too few respondents. Extra costs resulting from obtaining
excessive questionnaires in the main interview effort may
be greater than the costs for a few additional questionnaires
in the pretest.


Information Checking


How a pretest improved a particular question ina sur-
vey of settlers in the colonization project in Caqueta,
Colombia is illustrated as follows [48].





Original question:
Where did you live before youmovedhere?
Improved questions:
In which Department were you born?
Where did you live before moving to Caqueta?
Where did you live before moving to this farm?
The researcher wanted to know from which departments
the settlers had migrated to Caqueta, but the original ques-
tion only revealed information about therespondent's last
move which may have been within Caqueta and not from another
department. Even though questions were added, the results
were easier to interpret. Based on this researcher's infor-
mation needs, the first question had no value so he was forced
to choose between no question and three questions.
A pretest will assist the researcher to develop an effi-
cient but complete questionnaire. A poorly pretested set of
questions designed to obtain information about farm manage-
ment practices and production costs for potato producers
in Colombia illustrates this point.2 The respondents were
asked the number of hectares devoted to potato production
for the most recent year at three different points in the
questionnaire. At the beginning, producers were asked to
give total farm size and land use by crops, pasture, and
other classifications. Later in the interview they report-
ed on potato plantings for each eme.steA. This informa-
tion often did not agree with the first question because
of double counting. It was difficult to verify the re-
sponse because plantings in the first semester were usu-
ally much larger than in the second, so the extent of the
double counting was impossible to determine. And finally,
when queried about hectares harvested the area given was
usually slightly different from that previously used.
Could it be assumed that those hectares not harvested were


From a portion of a producer questionnaire used in
Colombia and summarized in [37].





lost to blight or drought? Perhaps, but it would be better
to be certain that the difference was not in part due to
either intentional or unintentional reporting error. Not
only was the duplication unnecessary, but the questions were
ambiguous. A better pretest could have minimized this dis-
crepancy by guiding the preparation of one comprehensive and
easily understood set of questions related to hectares of
potatoes seeded and harvested for the past year.
After completing the pretest, responses should be tab-
ulated and critically reviewed to determine whether the ques-
tions were understood clearly and whether the information
which resulted would help to resolve the problem. This step
frequently uncovers gaps in information, or responses which
are not in the best form for the analyses which are to be
undertaken. While the pretest may identify needed modifica-
tions in the questionnaire, it also provides an opportunity
to determine whether or not the responses are in a form such
that the hypotheses can be tested. The researcher should care-
fully consider what is being collected in the pretest and how
it can be used in the hypothesis testing and analysis phases
of the research.
Some research advisors insist that their students use
pretest data on a "practice run" through the analysis which
slows the research process, but only momentarily. Analyzing
pretest data can aid greatly in refining and even specifying
the exact analytical tools which typically are not given too
much thought until all of the data are collected. This may
also provide some ideas as to the format for the final pu-
blication. If these benefits are gained from analyzing pre-
test data then the saving of time at a later stage in the
research process will more than compensate for the early time
loss.
Often a pretest indicates that either too little or too
much information is being collected. At times, the pretest
may show that a certain type of information will not be avail--
able, and therefore, some modification will need to be made
in analyses, hypotheses, or objectives. More commonly, the
questionnaire may be gathering more information than is ne-





cessary which suggests that costs of getting the excess
should be carefully considered relative to potential uses
of the information.
Only when protests have shown that interpretational
problems are minimal and that the information can be obtained
in the form required, should the questionnaire be finalized
and the complete survey undertaken.


Time Difficulties


Because timing is so important, the pretest should be
used to help specify interview time problems; time of year,
month, week, and day must be carefully considered to fit
the respondents' work schedule.3 If, for example, one is
proposing to interview truckers at check stations or con-
sumers at a retail market the time element may be more cri-
tical than in interviews with producers. Retailers usually
prefer granting interviews when the fewest customers are in
the store. For small retailers, daytime interview can be
three or four times as long as an uninterrupted nightime in-
terview; but if an appointment cannot be obtained for non-
working hours, as is often true, the more lengthy daytime
interview may be necessary. Agricultural producers probably
will find harvest time to be inconvenient.
Numerous examples canbe cited but few guidelines can
be specified for timing interviews because each survey and
often each interview represents different situation. In
any case, should the respondent feel that the questionnaire
is completely irrelevant and waste of time, the responses
will lack credibility evenwhen the interviewer is fortunate
enough to complete the interview.



Mail questionnaires help resolve time problems but
often limit response quality and, due to low response rates,
require large samples. A bibliography concerning mail-
questionnaire research is found in [42].





Selecting and Training Interviewers


A well-designed and pretested questionnaire will not
yield good results if administered by an interviewer who is
poorly trained or who has a disagreeable, non-cooperative
and culturally or class biased attitude toward the respon-
dent. The contact made with the respondent will not only
influence the interview but also influence the respondent's
evaluation of the entity for whom the interviewer is working,
and his acceptance of action programs that might evolve from
the research recommendations. Requisites ofa good inter-
viewer include: 1) an interest in and an understanding of
the research project, 2) an interest in people and the
ability to communicate that interest and sincerity to a re-
spondent, 3) willingness and ability to follow instruc-
tions and definitions without regard for personal beliefs
or convictions, and 4) in general, good public relations
attitude.
Training is necessary to familiarize both experienced
and inexperienced interviewers with the problem to be stud-
ied, the objectives of the research project and the organiza-
tion sponsoring the work, the questionnaires, the respon-
dent selection procedures and the interviewing techniques.
An interviewer's manner of asking questions must be objec-
tive and he must be neutral and honestin recordingrespon-
ses. The most important goal of the survey is to get an
unbiased opinion or bit of data for each question. What-
ever the interviewer thinks of the respondent and his opin-
ions should not influence interviewer objectivity.
Interviewers should be instructed carefully on methods
for introducing the research project to the respondent. A
most difficult question to answer is respondent's inquiry
about the legality of the study. Letters of introduction
and any other documents from official and credible sources
should always be in the possession of interviewers. To es-
tablish respondent confidence, the introduction used by the
interviewer and the letter itself should explain that the





interview is confidential, and that the information sought
will be used to determine attitudes and characteristics of
groups for comparative purposes, and not to illustrate char-
acteristics of specific respondents.
Although the interview must be objective, the inter-
viewer must be given flexibility to obtain a useful response.
He should record specific comments and not vague or mean-
ingless generalities such as "because it is interesting" or
"I like it because it is good," Why is it interesting?
Why is it good? The "I don't know" response is one of the
most difficult to manage. One is not sure whether the re-
spondent really did not know, whether he did not understand
the question, or whether he did not want to respond for vari-
ous reasons. The respondent should be encouraged by the
interviewer to believe that an "I don't know" response is
not an admission of ignorance. A simple guess or an es-
timate calculated to suit what the respondent feels the
interviewer wants is unacceptable. The respondent, how-
ever, should not be encouraged to give an "I don't know"
response when he most likely can give a meaningful and hon-
est reply.


Verifying Primary Data


Verification of the data after it is collected is ne-
cessary before data processing and analysis begin. The re-
searcher must become fully aware of the limits and potential
uses of his data based upon the objectives of his research.
A careful review of data with well performed revisions at
this stage of the research process will reduce the chance
of costly errors.
Numerous and detailed verification activities are ne-
cessary so the researcher can be confident that the data
best measure the phenomena needed to fulfill the research
objectives, given the resource limitations placed upon the
project. The verification and preparation process must con-
sider techniques for handling missing observations, falsi-





fled data, completely inaccurate measures, and so on, as well
as the necessary conversions where measuring units have dif-
fered. Often the required transformations corrections, and
general manipulations performed on data are dictated by the
type of facilities available for processing. Computer pro-
cessing is not necessary for all research, particularly when
projects are small and calculators are readily available.
Both time and monetary costs for each alternative should be
considered along with the type of analysis desired and the
degree of accuracy needed. But regardless of the processing
facilities and techniques to be employed, well specified me-
thods for verifying and coding datawill improve efficiency
in research resource use.
During field data collection and while verifying and
coding results, the researcher should accurately record his
collection and verification techniques. This record, com-
monly called a code book, is also oriented to describing data
collection and verification techniques and it may also in-
clude some data refinement such as frequency distributions,
means, standard errors and so on. It not only serves as
a guide to his present work, but also serves to indicate
in detail what the data represent for use in further re-
search efforts.

Verifying and Using Secondary Data


The researcher usually has no control over secondary
data measurement but he has the responsibility for checking
very carefully to determine exactly how it was derived, the
nature of the aggregations made and if the data will meet
the needs of his research [65]. Secondary sources can be
classified into two major types: 1) regular and long-run
measures of phenomena such as prices, income, production,
rainfall, and temperature; and 2) less regular and, in
general, short-run measures of phenomena more often associa-
ted with another person's research such as crop response
to improved inputs, consumer attitudes, and management
characteristics.





Time series data can often be difficult to use and
verify because they are secondary and not necessarily de-
signed for a specific research project. Because time series
frequently cover extended time periods, collection is per-
formed by an agency which is responsible for maintaining
continuity in the collection process. No particular person
is responsible for collecting these data over the years, but
certain procedures are established and revised occasionally
to accurately and adequately measure the particular pheno-
mena under study. Nevertheless, definitions should be
checked carefully so that the researcher can decide what
the data in question are supposed to measure, and since he
has no control over the collection of these data, he must
satisfy himself that they in fact do measure the phenomena
in which he is interested.
Comparability may be the most common difficulty in using
times series data. This refers to 1) comparability of dif-
ferent time series which purport to measure the same phe-
nomena and 2) comparability of different periods within the
same series. For example, due to plant breeding and food
processing programs, the corn produced and marketed fifty
years ago and the corn produced and marketed today are virtu-
ally two different products. A price series for corn covering
this period of time is not comparable during the entire period.
Coupled with product changes in a price series is the equally
difficult problem of non-comparability in currency values
caused by price inflation or deflation in the national economy.
A serious comparability problem, and one that is dif-
ficult to detect within a time series, is a change in defi-
nition. For example, a change in quality standards will af-
fect a price series, but may not necessarily be specified.
A change in the point of measurement such as the location of
price determination from the farmer-assembler level to the
wholesaler-retailer level will influence the value of the
economic variable in question. In census data one may find
a change in the definition of a farm. Similarly, changes
in the population of a city may in part be due to changes in
the boundary lines.





Non-comparability between series attempting to measure
the same phenomena is common particularly in developing coun-
tries because time series measurement systems have often not
been standardized under the authority of one agency. Unfor-
tunately, in many cases these entities neither clearly de-
fine the phenomena to be measured nor the precise points and
times of measurement. And when the points and times are de-
fined, a change in definition may not be spelled out after
it is made.
As an example, consider the separate series of potato
production data compiled by the Caja Agtraia (a public ag-
ricultural credit agency) in Colombia and IDEMA (a public
agricultural marketing agency) [36, p. 230]. These series
are vastly different, with the production data of IDEMA
averaging about 40 percent lower than the data of the Caja
Agratia. This difference is probably due to differences
in methods of measurement of the series. The Caja Agratia
primarily develops their series from producer loan data,
while that-of IDEMA is based on measures taken in rural
markets. Thus, Caja Agatoia more closely estimates total
production and IDEMA measures the production entering com-
mercial channels. If the researcher is interested in the
volume of commercial sales of potatoes, the IDEMA data prob-
ably are more accurate. On the other hand, if the researcher
wished to estimate per capital potato consumption, including
both rural and urban consumers, the IDEMA series would under-
estimate this variable by about 40 percent less losses and
seed requirements.
Where time series is needed but unavailable or pos-
sibly inappropriate for a specific problem, cross-section
data sometimes can be substituted. Cross-section data (ex-
perimental and non-experimental) represent phenomena mea-
sured only at one point in time or a limited number of times.
One means of using cross-section data to simulate longevity
is in questionnaire research where respondents recall infor-
mation concerning an event at present, last year, five years
ago, and soon. Care must be observed in interpreting these





measures because of what has been termed a telescoping bias.
That is, the tendency to completely overemphasize or under-
emphasize certain phenomena by projecting present conditions
to previous points in time while forgetting others that may
have influenced these observations.


Summary


The success of non-experimental data collection rests
upon the ability of the researcher to accurately sample the
defined population and, once the sample is drawn, communi-
cate with the selected respondents. In designing the ques-
tionnaire which is the means of obtaining information from
the respondents, two important communication problems must
be considered: 1) differences in terminology between various
groups, and 2) cultural differences in beliefs and values.
Pretesting the questionnaire under actual field conditions
can provide information both about its effectiveness as a
data gathering tool and information on the population which
can help in establishing sample size.
As in the case of experimentation, guidelines for op-
timum, sample selection procedures and questionnaire design
in non-experimental research can be stated, but in applied
research it is important that the researcher remain flexible
in his attitude. Scientific perfection can serve as anorm,
but the researcher must remember that for the client, it is
almost always better to have some information to help him
make his decisions than to have no. information except that
the researcher is still designing a better questionnaire or
trying to decide on the best means of choosing the respon-
dents.













CHAPTER VI


DATA UTILIZATION -- WHAT DOES IT ALL MEAN?


The real skill of the applied researcher comes into play
after the collection of the data has been completed. Exper-
ience and imagination have a particularly high payoff in the
analysis and the interpretation of the data and can make a
difference between a usefulproject and one which ends up in
a file drawer. It is in this process that the researcher
finally comes down to the point of determining what the data
entail; data do not "speak for themselves" but must be inter-
preted and analyzed. Theresearcher must draw conclusions
from the analysis and in the end make recommendations to his
client to help in resolving the problem that originated the
project. This, of course, is thereason for undertaking app-
lied research in the first place. No amount of planning, no
elegant data collection procedures, and no sophisticated an-
alyses are goingto help the researcherwho is too timid when
the moment of truth arrives to utilize all his information,
draw meaningful conclusions and make appropriate recommen-
dations to the client.1
When this moment arrives, the client is expecting a use-
ful product and the researcher is the most knowledgeable per-
son available to him. At the conclusion of this project, the
researcher should know more about the subject being studied
than anyone else with whom the client has contact. If this
is not so, the client should have gone elsewhere for his in-
formation.And if the client had not needed the information


1For references particularly concerned with interpre-
tation and communication of research results see [21,4,57,78].




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