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CRITICAL ANALYSIS OF CRAFT SKILLS ASSESSMENT TESTING INSTRUMENTS By SUSANNA DONATA CATALANO A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN BUILDING CONSTRUCTION UNIVERSITY OF FLORIDA 2004 Copyright 2004 by Susanna Donata Catalano To my loving family: Mom, Dad, and RoRo. ACKNOWLEDGMENTS I thank my family for their unconditional love and support. Words can not capture how thankful I am to have been blessed with two wonderful parents, Remo and Gladys Catalano. They have given me extraordinary support throughout all aspects of my entire college career. My sister, RoRo, I thank for her words of wisdom and her willingness to stop whatever she is doing to encourage and motivate her little sister. I thank my committee advisors for their help and insight toward my thesis. Special thanks go to Dr. Robert Cox for his knowledge, encouragement and counseling, which were all key components in helping me complete my thesis. I thank Dr. Raymond Issa for his knowledge and continued support. I would also like to thank Dr. Leon Wetherington. I thank the National Center for Construction Education and Research for providing the NCCER Training Research conducted by Dr. Roger Liska and Yogesh V. Bansal from the Construction Science and Management Department at Clemson University. Special thanks go to Dr. George Casella from the Department of Statistics and Dr. Robert Stroh from the College of Design, Construction and Planning at the University of Florida for their statistical advice. Also, special thanks go to the UF ETD Computing Help Desk staff and Vijay Villavan for his expertise in helping to reformat my thesis. TABLE OF CONTENTS page A C K N O W L E D G M E N T S ................................................................................................. iv LIST OF TA BLE S ........... ....................... ......... ......... ..............vii LIST OF FIGURES ................................. .. ... .. ..................x A B STR A C T ........................................................................................ ....... ..................xviii CHAPTER 1 IN TR O D U C T IO N ............................................................. .. ......... ...... ..... State ent of P problem ........................................................... ......... ............ 1 O b j e c tiv e s ................................................................. ...................................... 1 M eth o d o lo g y ....................................................................................... 1 Scope and Lim stations ........................................ ..... ................ .. 3 O v erview of R research ........................................................... ........ ............... 3 2 L ITER A TU R E R E V IEW .................................................................... ....................4 Training Program s ...................... ............................ .. ......... ....... 5 U union P program s .................................................................................. .. 6 N onU nion Program s........... .......................................................... ............... A ssessm ent and Evaluation ........................................ ................................. 9 Sum m ary of Literature R review ......................................................... ............... 13 3 M E T H O D O L O G Y ...................................... ................................... .................... ... 14 Introduction ......................................................................................................14 T h e P ro c e s s ............................................................................................................ 1 4 A acquisition of D ata........... ........................................ .................. .. .... .. .... 14 L iteratu re R ev iew ......................................................................... ...... ... 15 D ata A n aly ses ................................................................... ............... 15 C conclusion ...................1................. 17 v 4 DATA AND ANALYSIS........................................................................ 18 D ata E x p lan atio n .............................................................................. .......... .. .. 18 Statistical F am iliarity ......................................................................... ........ .......... 19 Tables of Statistical A nalysis......................................................... .. ............... 21 Review and Discussion of Data from Average Scores.............................................24 Review of Data for Average Scores with 010 Years of Experience ....................28 H isto g ram s ...................... .. .. ......... .. .. .............................................. 3 0 Sum m ary of D ata A analysis ...... ............. ................ ....................... ............... 35 5 CONCLUSIONS AND RECOMMENDATIONS ............................................. 39 Sy n op sis of R research ................ ..... ......... .. .. ........................ ....................39 Recommendations for Future Research.................... ...........................44 APPENDIX A: TABLES OF STATISTICAL ANALYSIS ...................................... ............... 45 T ables of A v erage Scores ......................................... ....................... ....................56 B: GRAPHS OF AVERAGE SCORES.................................................................... 89 Data of Average Scores with 010 Years of Experience ............... ............... 120 LIST O F R EFER EN CE S ......... ............................. .............................. ............... 168 BIOGRAPHICAL SKETCH .............. ............................................................. 171 LIST OF TABLES Table pge 21 New Apprentices in Construction by Year and Program Type..............................6 4 1 A ll T rad es .............................. .......... ..... .......................................2 2 42 Average Scores by Craft and Categories....................................... ............... 24 Ai Abnormal Operating ConditionsControl Center................... .......................... 45 A2 Abnormal Operating ConditionsGas..................... .... ......................... 45 A3. Abnormal Operating ConditionsGeneral................................. ............. ............ 46 A4 Boiler Technician ............ ...... ..... ......... ............ ........ ... .............46 A 5 B o ilerm ak er ...................... .. ............. .. ................................................4 6 A 6 C om m ercial C carpenter ..................................................................... ..................47 A 7 C om m ercial E lectrician ......................................... .............................................47 A8. Corrosion Prevention Field Technician 1Installation.................. .............. 47 A9 Corrosion Prevention Field Technician 1Measurement ......................................48 A10 Corrosion Prevention Field Technician2 ..................................... .................48 A11 Corrosion Prevention Field Technician3 ..................................... .................48 A12 Electrical and Instrumentation Pipeline Technician ..........................................49 A13 Field and Control Center Operations Technician.............. .... ...............49 A 14 G as M maintenance Specialty ........................................................... .....................49 A 15 G as Pipeline O operations ......... ................. ................... ................... ............... 50 A16 HVAC .............. ........ ......... ..... ................50 A17 Industrial Carpenter.............................................. 50 A 18 Indu trial E electrician ........................................................................ .................. 5 1 A 19 Industrial Insulator .......................................... .. .. ............. ......... 51 A 20 Indu strial Ironw orker........................................................................ ..................5 1 A21 Industrial M maintenance Electrician...................................... ......................... 52 A22 Industrial M maintenance M echanic ........................................ ........................ 52 A 23 Indu trial M illw right ........................................................................ .................. 52 A24 Industrial Painter .......................................... .. ................... 53 A 2 5 Indu trial P ipefitter.......................................................................... ................... 53 A 26 Instrum entation F itter...................................................................... ...................53 A27 Instrumentation Technician................................................ 54 A 28 M echanical Pipeline Technician ........................................ ......................... 54 A 29 N onD destructive Testing ................................................ .............................. 54 A 30 Pipeline M maintenance Technician ........................................ ........................ 55 A 31 Scaffold B builder ............................................ .. .. ........... ......... 55 A 32 A ll T rades ........................................................................................................55 A33 Average Scores by Craft and Categories....................................... ............... 56 A34 Abnormal Operating ConditionsControl Center: TTest and FTest...................57 A35 Abnormal Operating ConditionsGas: TTest and FTest.....................................58 A36 Abnormal Operating ConditionsGeneral: TTest and FTest.............................59 A37 Boiler Technician: TTest and FTest...................................................................60 A 38 B oilerm aker: TTest and FTest........................................ ........................... 61 A39 Commercial Carpenter: TTest and FTest ................................... .................62 A40 Commercial Electrician: TTest and FTest.................................. ...............63 A41 Corrosion Prevention Field Technician 1Installation: TTest and F T e st ............................................................................. 6 4 A42 Corrosion Prevention Field Technician 1Measurement: TTest and F T e st ............................................................................. 6 5 A43 Corrosion Prevention Field Technician2: TTest and FTest ..............................66 A44 Corrosion Prevention Field Technician3: TTest and FTest ..............................67 A45 Electrical and Instrumentation Pipeline Technician: TTest and FTest..................68 A46 Field and Control Center Operations Technician: TTest and FTest....................69 A47 Gas Maintenance Specialty: TTest and FTest...................................................70 A48 Gas Pipeline Operations: TTest and FTest................................. ...... ...............71 A 49 H V A C : TTest and FTest............................................... ............................. 72 A50 Industrial Carpenter: TTest and FTest........................................ ............... 73 A51 Industrial Electrician: TTest and FTest ...................................... ............... 74 A 52 Industrial Insulator: TTest and FTest ........................................ .....................75 A53 Industrial Ironworker: TTest and FTest............................ ...................76 A54 Industrial Maintenance Electrician: TTest and FTest......................................77 A55 Industrial Maintenance Mechanic: TTest and FTest.............. ... ........... 78 A56 Industrial Millwright: TTest and FTest ...................................... ............... 79 A57 Industrial Painter: TTest and FTest ............................................ ............... 80 A58 Industrial Pipefitter: TTest and FTest......................................... ............... 81 A59 Instrumentation Fitter: TTest and FTest........................................................82 A60 Instrumentation Technician: TTest and FTest....................... ...............83 A61 Mechanical Pipeline Technician: TTest and FTest ............................................84 A62 N onDestructive Testing: TTest and FTest ........................................ ................85 A63 Pipeline Maintenance Technician: TTest and FTest ............................................86 A64 Scaffold Builder: TTest and FTest ............................................. ............... 87 A 65 A ll Trades: TTest and FT est...................................................................... .. .... 88 LIST OF FIGURES Figure page 11 Flow chart of M ethodology......... ................. ................... ................. ............... 2 21 An Example of the NCCER Craft Assessment Program Overview..........................8 22 Distribution of Construction Workers Who are Racial Minorities ..................... 11 23 Distribution of Hispanic Construction Workers............... .... .................12 41 Graph of Abnormal Operating Conditions Control Center................................25 42 Graph of Corrosion Prevention Field 1Measurement...........................................26 43 Graph of Gas M maintenance Specialty.................................................. ............... 27 44 Graph of Electrical and Instrumentation Pipeline Technician .............. ...............28 45 Graph of Abnormal Operating ConditionsGeneral..............................................29 46 Histogram of All Crafts Including All Categories. ...............................................30 47 Histogram of Category All Comparing Average Scores, Frequency, and Cumulative Percentages .................. .................................... 48 Histogram of Category With Training Comparing Average Scores, Frequency, and Cumulative Percentages ...................................... ............... 32 49 Histogram of Category With NCCER Training Comparing Average Scores, Frequency, and Cumulative Percentages ...................................... ............... 33 410 Histogram of Category Without Training Comparing Average Scores, Frequency, and Cumulative Percentages ...................................... ............... 34 411 Graph of Abnormal Operating Conditions Control Center Comparing C oefficient of V ariation. ........... ........... ........ .... .......... ....... ................. 35 51 NCCER Assessment Test Questionnaire on Training .......................... ..........40 52 Question on Form al Training. ............................................................................41 53 Question on By W hom ................................................. ................................ 42 54 Question on Experience Type. ............................................................................ 42 55 Question on Education Level. ............................................................................43 56 Q u estion on A ge ..... .... ... ............................................... .................. .... 43 57 Question on Have You Taken This Test Before. ...........................................43 Bl Graph of Abnormal Operating ConditionsControl Center Comparing Average Scores Between All, With Training, With NCCER Training, and W without T raining ............................................................................ ................ .. 89 B2 Graph of Abnormal Operating ConditionsGas Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training.........90 B3 Graph of Abnormal Operating ConditionsGeneral Comparing Average Scores Between All, With Training, With NCCER Training, and W without Training. ..................... ...... ............................... ........... .... 91 B4 Graph of Boiler Technician Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training .....................................92 B5 Graph of Boilermaker Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training ............................93 B6 Graph of Commercial Carpenter Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training ............................94 B7 Graph of Commercial Electrician Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training ............................95 B8 Graph of Corrosion Prevention Field Technician 1Installation Comparing Average Scores Between All, With Training, With NCCER T raining,and W without Training ..................................................... .....................96 B9 Graph of Corrosion Prevention Field 1Measurement Comparing Average Scores Between All, With Training, With NCCER Training, and W without T raining ....... .... ...... .... ........ ...................... .... ................ .. 97 B10 Graph of Corrosion Prevention Field Technician2 Comparing Average Scores Between All, With Training, With NCCER Training,and W without T raining .................................................................. ........ ....... .. 98 B11 Graph of Corrosion Prevention Field Technician3 Comparing Average Scores Between All, With Training, With NCCER Training, and W without Training ......................... ........... ........ ...............99 B12 Graph of Electrical and Instrumentation Pipeline Technician Comparing Average Scores Between All, With Training, With NCCER Training, an d W ith out T raining ....................................................... .......... .................... 100 B13 Graph of Field and Control Center Operations Technician Comparing Average Scores Between All, With Training, With NCCER Training, and W without T raining ....... .... ...... .... ........ .................... .... ................ .. 10 1 B14 Graph of Gas Maintenance Specialty Comparing Average Scores Between All,With Training, With NCCER Training, and Without Training .....................102 B15 Graph of Gas Pipeline Operations Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training .................103 B16 Graph of HVAC Comparing Average Scores Between All, With Training, W ith NCCER Training, and W without Training ............................... ... ............... 104 B17 Graph of Industrial Carpenter Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training ............................105 B18 Graph of Industrial Electrician Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training ............................106 B19 Graph of Industrial Insulator Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training .............................107 B20 Graph of Industrial Ironworker Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training .............................108 B21 Graph of Industrial Maintenance Electrician Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training.......109 B22 Graph of Industrial Maintenance Mechanic Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training ......................110 B23 Graph of Industrial Millwright Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training ............................ 111 B24 Graph of Industrial Painter Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training ..........................112 B25 Graph of Industrial Pipefitter Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training ..........................113 B26 Graph of Instrumentation Fitter Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training .............. ...............114 B27 Graph of Instrumentation Technician Comparing Average Scores Between All,With Training, With NCCER Training, and Without Training ....................115 B28 Graph of Mechanical Pipeline Technician Comparing Average Scores Between All, With Training, With NCCER Training, and W without Training ............. ... ............ ....................... ...... ....116 B29 Graph of NonDestructive Testing Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training ......................117 B30 Graph of Pipeline Maintenance Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training .................................... 118 B31 Graph of Scaffold Builder Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training ..........................119 B32 Graph of All Trades Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training ...........................120 B33 Graph of Abnormal Operating Conditions Control Center Comparing Years of Experience and Average Scores Between All, With Training, W ith NCCER Training, and W without Training .................................................121 B34 Graph of Abnormal Operating Conditions Gas Comparing Years of Experience and Average Scores Between All, With Training, With NCCER T raining, and W without Training .................................................. .....................122 B35 Graph of Abnormal Operating Conditions General Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without Training ........................................ ......................... 123 B36 Graph of Boiler Technician Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without T raining ....... .... ...... .... ........ .................... .... ................ .. 124 B37 Graph of Boilermaker Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and Without Training ......125 B38 Graph of Commercial Carpenter Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without T raining ....... .... ...... .... ........ .................... .... ................ .. 126 B39 Graph of Commercial Electrician Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without T raining ....... .... ...... .... ........ .................... .... ................ .. 127 B40 Graph of Corrosion Prevention Field Technician 1Installation Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and Without Training ...........................128 B41 Graph of Corrosion Prevention Field Technician 1Measurement Comparing Years of Experience and Average Scores Between All, With Training, W ith NCCER Training, and W without Training .................................................129 B42 Graph of Corrosion Prevention Field Technician2 Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without Training ........................................ ......................... 130 B43 Graph of Corrosion Prevention Field Technician3 Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without Training ........................................ ......................... 131 B44 Graph of Electrical and Instrumentation Pipeline Technician Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without Training .................................... ......... ......... 132 B45 Graph of Field and Control Center Operations Technician Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without Training .................................... ......... ......... 133 B46 Graph of Gas Maintenance Specialty Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without T raining ....... .... ...... .... ........ .................... .... ................ .. 134 B47 Graph of Gas Pipeline Operations Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without Training ............. ... ............ ....................... ...... ....135 B48 Graph of HVAC Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and Without Training .......136 B49 Graph of Industrial Carpenter Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without T raining ......... ................ .................... .... ................ .. 137 B50 Graph of Industrial Electrician Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without T raining ......... ................ ............................................ .. 138 B51 Graph of Industrial Insulator Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without T raining ...... ....................................................... ................ ............ 139 B52 Graph of Industrial Ironworker Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W ith ou t T rain in g ...... .. .... .. .... .... .... .. ........ .. .................... .... ................ .. 14 0 B53 Graph of Industrial Maintenance Electrician Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without Training ........................................ ......................... 141 B54 Graph of Industrial Maintenance Mechanic Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without Training ........................................ ......................... 142 B55 Graph of Industrial Millwright Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without T raining ....... .... ...... .... ........ .................... .... ................ .. 143 B56 Graph of Industrial Painter Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without Training ........................................................ ............ 144 B57 Graph of Industrial Pipefitter Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without T raining ....... .... ...... .... ........ .................... .... ................ .. 145 B58 Graph of Industrial Fitter Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without T raining ....... .... ...... .... ........ .................... .... ................ .. 146 B59 Graph of Instrumentation Technician Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and Without Training ................ ....... ......... ................ .. 147 B60 Graph of Mechanical Pipeline Technician Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W ith ou t T rain in g ........ .... ........ .. .. .. .. ...... .................... .... ................ .. 14 8 B61 Graph of NonDestructive Testing Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without T raining ....... .... ...... .... ........ .................... .... ................ .. 149 B62 Graph of Pipeline Mechanical Technician Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without T raining ....... .... ...... .... ........ .................... .... .............. 150 B63 Graph of Scaffold Builder Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and W without Training ............. ... ............ ....................... ...... ....151 B64 Graph of Coefficient of Variation of Abnormal Operating Conditions Control C en ter. .......................................................................... 15 2 B65 Graph of Coefficient of Variation of Abnormal Operating ConditionsGas................. ......... ................................... ... ........ 152 B66 Graph of Coefficient of Variation of Abnormal Operating ConditionsG general ......................... ....... .... .. ...... ........... ... 153 B67 Graph of Coefficient of Variation of Boiler Technician..................................153 B68 Graph of Coefficient of Variation of Boilermaker...........................................154 B69 Graph of Coefficient of Variation of Commercial Carpenter ........... ..............154 B70 Graph of Coefficient of Variation of Commercial Electrican.............................155 B71 Graph of Coefficient of Variation of Corrosion Prevention Field T technician 1Installation ......... ................................................... ............... 155 B72 Graph of Coefficient of Variation of Corrosion Prevention Field Technician 1M easurem ent. ........................................... ............................. 156 B73 Graph of Coefficient of Variation of Corrosion Prevention Field T ech n ician 2 ......................................................................................... 156 B74 Graph of Coefficient of Variation of Corrosion Prevention Field Technician3 ................ ...... ... ............. ....... .......... ......... 157 B75 Graph of Coefficient of Variation of Electrical and Instrumentation Pipeline Technician. ....................... .................. .......................... 157 B76 Graph of Coefficient of Variation of Field and Control Center O operations T echnician.......... .......................................................... .... .... ... ... 158 B77 Graph of Coefficient of Variation of Gas Maintenance Specialty.......................158 B78 Graph of Coefficient of Variation of Gas Pipeline Operations ...........................159 B79 Graph of Coefficient of Variation of HVAC. ............... .......................159 B80 Graph of Coefficient of Variation of Industrial Carpenter................................160 B81 Graph of Coefficient of Variation of Industrial Electrician.............................160 B82 Graph of Coefficient of Variation of Industrial Insulator. ................................... 161 B83 Graph of Coefficient of Variation of Industrial Ironworker. .............................161 B84 Graph of Coefficient of Variation of Industrial Maintenance E lectrician...................................................... ................... ........ ...... 162 B85 Graph of Coefficient of Variation of Industrial Maintenance M mechanic. ......................................................................... 162 B86 Graph of Coefficient of Variation of Industrial Millwright .............. ...............163 B87 Graph of Coefficient of Variation of Industrial Painter ............ ................163 B88 Graph of Coefficient of Variation of Industrial Pipefitter.................................... 164 B89 Graph of Coefficient of Variation of Instrumentation Fitter ..............................164 B90 Graph of Coefficient of Variation of Instrumentation Technician.........................165 B91 Graph of Coefficient of Variation of Mechanical Pipeline T technician. ........................................................ .......... ...... 165 B92 Graph of Coefficient of Variation of NonDestructive Testing ...........................166 B93 Graph of Coefficient of Variation of Pipeline Maintenance.............................166 B94 Graph of Coefficient of Variation of Scaffold Builder ........................................167 B95 Graph of Coefficient of Variation of All Trades..............................167 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science in Building Construction CRITICAL ANALYSIS OF CRAFT SKILLS ASSESSMENT TESTING INSTRUMENTS By Susanna Donata Catalano December 2004 Chair: Robert Cox Cochair: R. Raymond Issa Major Department: Building Construction Apprenticeships are programs where workers gain a broad amount of skills necessary for their craft. Not only can workers take formal training courses, but craftworkers may gain the skills for their craft from employers and other skilled craftsmen on the jobsite. The purpose of this thesis is to compare the assessment test scores of formally trained craftworkers compared to those test scores of other craftworkers. This thesis further examines the assessment test scores of thirtyone crafts from the National Center for Construction Education and Research (NCCER) Training Research conducted by Dr. Roger Liska and Yogesh V. Bansal from the Construction Science Management Department at Clemson University. The topics covered in this thesis are an introduction to the research; literature review on apprenticeship training programs and demographics of craftsmen; the xviii methodology of the thesis; data and analysis of the results; conclusions and recommendations based on the results; and appendices of all tables and graphs representing all the crafts in this thesis. CHAPTER 1 INTRODUCTION Statement of Problem The purpose of this thesis is to further examine the assessment test scores of thirty one crafts from the National Center for Construction Education and Research (NCCER) Training Research conducted by Dr. Liska and Yogesh V. Bansal from the Construction Science Management Department at Clemson University. This thesis will compare the assessment test scores of formally trained craftworkers compared to those test scores of other craftworkers. Objectives Apprenticeships are programs where workers gain a broad amount of skills necessary for their craft. Not only can workers take formal training courses, but craftworkers may gain the skills for their craft from employers and other skilled craftsmen on the jobsite. Construction workers may start the workforce with little or no training which can lead to problems in the industry as it continues to grow. Before this thesis began, hypotheses were formed regarding the scores of formally trained individuals compared to individuals without formal training: 1. Formally trained craftworkers will have higher assessment scores. 2. The assessment test scores will show a gradual improvement with an increase in the years of experience. Methodology This thesis will use reported data conducted by Dr. Roger Liska and Yogesh V. Bansal, which will be referred to as the Liska Study. A statistical analysis will be performed on this data along with a review of research on material relating to this topic will be explored. Figure 11 represents the methodology taken in this thesis: NCCER 5 5 Train g Statistical Analysis 7 Research 1. FCompare Results of Conducted Ass t Statistical Fmdmigs by Dr Test Data with Hypotheses and Roger e te seset Tes wLiterature Find gs Llaccompska anied by Microsoft Excel files. The Microsoft Excel files were organized by i separate fes Literature Review Yogesh V .. .. Bansal Figure 11. Flowchart of Methodology From the methodology flowchart, number 1 is the NCCER Training Research conducted by Liska and Bansal. In number 2, the Assessment Test Data from NCCER was provided in book form accompanied by Microsoft Excel files. The Microsoft Excel files were organized by separate files for each individual craft. In number 3, the data from NCCER Training Research was reviewed. In each crafts' Excel file, the data was organized into tables and graphs. The Liska Study displayed the statistical analysis by each craft. The categories provided were the following: All, With Training, Training With NCCER and Years of Experience. Within the categories: All, With Training and With NCCER Training, there were two subcategories: Count and Average Score. The data from the tables were also put into graphs comparing years of experience with the average scores. In the number 4 part of the methodology flowchart, all the separated files from the reported data from the Liska Study were compiled into one file. Compiling the separate files into one file made the data more manageable to statistically analyze. Each craft was kept separate from the next craft by the listing each craft by name. In numbers 5 and 6, a statistical analysis was performed along with a literature review of topics of this subject. The statistical analysis used is called descriptive statistics. A detailed description of the statistical process is discussed in Chapter 3 of this thesis. After the statistical analysis and literature review, a comparison of the data results with the hypotheses and literature findings were performed which are number 7 in the flowchart of methodology. At this point, number 8, conclusions and recommendations are accomplished by summarizing the findings from the analysis performed. Scope and Limitations The purpose of this thesis is to compare the assessment test scores of formally trained craftworkers compared to those test scores of other craftworkers. The scope is limited by the Liska Study. The limitations are the data reported by the Liska Study on training. The data provided by the Liska Study were not accompanied with a written description of their methodology for their research. Given these limitations, the results and conclusions are limited to only the data reported in the NCCER Training Research. Overview of Research Chapter 2 of this study discusses the literature review on apprenticeship programs in the construction industry. Chapter 3 further explains the methodology used to perform this analysis of test scores among trained and nontrained craftworkers. The data and analysis and discussion of results is found in Chapter 4. The conclusions and recommendations is located in Chapter 5. CHAPTER 2 LITERATURE REVIEW In the construction industry, workers may enter the workforce without any formal training. Workers acquire their skills by apprenticeships, by other employee provided training or by informal onthejob experience. The opportunities for education and training in our industry today our endless, and the need for continuing education is critical as our industry continues to grow and as construction becomes more complex (Nasvik 2002) Apprenticeship programs provide apprentices with extensive skills for their trade. Apprenticeship combines employment and training in a formal framework whereby a worker acquires broadbased skills required for practicing a trade via onthejob training (Bilginsoy 2003). Apprentices will usually accept lower wages during their training, because the high cost of the training is usually provided by the employer. The employer will eagerly pay for training since they can get back their costs later by highly trained apprentices that are more proficient in the trade. Workers pick up skills by working with more experienced workers and through instruction provided by their employers. As they demonstrate their ability to perform tasks they are assigned, they move to progressively more challenging work. As they broaden their skills, they are allowed to work more independently, while responsibilities and earnings increase (Bureau of Labor Statistics 2004). With more apprentices in a program and completing the training, the more highly skilled workers with higher productivity will be performing on the jobsite. The idea behind this arrangement is for the apprentice not to quit the training program before the employer can receive their return on investment. More companies are willing to help the construction industry grow in a more productive and safer way by means of training. One employer, Building One, pays their workers $6 an hour during first three weeks of training and then they receive a $1.50 raise in the forth week. After six weeks, they get another raise to $8.50 and become part of the formal 8,000hour company apprenticeship program that takes about four years to complete with a $2,000 bonus for completing the entire apprenticeship (Krizan 1999). Not only are companies willing to pay for training, but some companies will pay for their workers' transportation and lodging during intensive training sessions which will last a few weeks. The construction industry's challenge is to attract and encourage individuals to work in this industry. Many individuals view the construction industry as undignified, filthy, and with minimal wages. According to sources, in the United States, seven out of ten jobs require trade skills, not college (Builders Guild 2004). The construction industry is large and will continue to grow, which means more skilled workers will be needed. Construction is the secondlargest industry in the nation, employing around 8 million workers who build almost $800 billion in new structures (Grogan 2000). Training Programs The apprenticeship programs that meet the federal standards register with the Bureau of Apprenticeship Training, BAT, of the Department of Labor or the BAT recognized State Apprenticeship Councils, SACs. These organizations promote training in the construction industry. These programs are organized either jointly by trade unions and employers signatory to collective bargaining agreement in the organized sector, or unilaterally by employers in the openshop sector (Bilginsoy 2003). Training in the construction industry is offered by union and nonunion affiliations, also known as joint and nonjoint programs. Table 21 below is an example of the breakdown of new apprentices affiliated with union and nonunion programs. Table 21. New Apprentices in Construction by Year and Program Type (Building and Construction Trades Department AFLCIO 2003). TOTAL REGISTRATIONS UNION REGISTRATIONS NONUNION REGISTRATIONS 1992 23,937 70.8% 29.2% 1993 28,034 73.2% 26.8% 1994 34,677 71.8% 28.2% 1995 28,340 73.2% 26.8% 1997 43,303 69.5% 30.5% 1998 47,826 70% 30% 1999 56,713 71.2% 28.8% 2000 63,633 71.8% 28.2% 2001 60,131 70.8% 29.2% 1989 467,980 71.6% 28.4% 2001 Union Programs Union apprenticeship programs contribute a large portion of skilled workers in the construction industry. According to 2003 labor statistics, unions enrolled 7,285 persons or 83 percent of people in construction apprenticeships (Vicent 2004). There are several types of joint apprenticeship programs across the United States. Most of the programs contribute a predetermined amount into the training fund per hour of labor employed (and hence the training costs are factored into the bids) and hire apprentices; unions provide training coordinators, instructors, and participate in the administration of the program; and trainees accept apprenticeship wages (Bradley 2002). The apprentices of union programs will usually earn half the wage amount of a skilled worker during their training, and upon completion will earn the full wage amount of a skilled worker, journeyman. The workers also receive benefits when they are participating in a joint apprenticeship program. The unions negotiate wages and benefits high enough to encourage workers to make construction a career; because of high quit rates, nonunion firms that pay less well must continually retrain novices (Bradley 2002). Unions will negotiate with contractors to formulate the proper training program for apprentices. Most of the programs integrate onthejob training with classroom education. The union apprenticeship programs differ in length of duration between two to five years of training. These programs usually combine structured, craft related classroom instruction, 144 hours/year minimum, with onthejob training under the supervision of an experienced, journey level worker (Libert 2004). NonUnion Programs The National Center for Construction Education and Research. The NCCER is a notforprofit 501(c)(3) education foundation founded in 1995 by 11 of the world's largest and most progressive construction companies and several national construction associations (National Center for Construction Education and Research 2002). The NCCER has developed a training program called the Contren Learning Series. This program enables individuals to customize their career path in construction by allowing them to choose which craft they want to learn. The Contren Learning Series has a curriculum for over 30 craft trades. Contren Learning Series curricula offers both perfectbound and modular formats permits a school to customize their construction program on either a straight craft track, such as carpentry, electrical, welding, etc., or on a general track by combining modules from a variety of trades (Prentice Hall 2004). The programs are developed from collaborations within the construction industry to create skill standards known throughout the industry. Since it is competency based, there are written and performance tests for each module in the Contren Learning Series. There are two course paths available to individuals, see Figure 21. The Craft Assessment path is for a craftsperson who is experienced and the Craft Training path is for an entry level craftsperson. From each path, a craftsperson has the opportunity to receive a certificate of recognition or to be certified or receive a certified plus 1 Assessed Training Prescribed Optional Figure 21. An example of the NCCER Craft Assessment Program Overview (National Center for Construction Education Research 2002). recognition. Taking the Craft Assessment path, an experience craftsperson will take a journey level assessment and results will be given. From this point, an option to take a written test or take the Contren Learning Series is arranged. If the craftperson takes the written test and passes, they become certified. If they want to become certified plus a performance verification is taken. If an individual does not want to take the written assessment tests, the certificate of recognition is achievable. The Associated General Contractors of America. The AGC of America was the first formal training program to be acknowledged by BAT. In 1981, the U.S. Department of Labor's Bureau of Apprenticeship and Training (BAT) recognized the AGC Model for Unilateral Trainee Program Standards (Associated General Contractors of America 2004). The AGC of America apprenticeship program allows individuals to participate in the program at their own pace. They offer several advantages that make it more attractive to young workers than more traditional timebased apprenticeship agreements. The programs are individualized, and allows workers to advance at an accelerated pace, as they demonstrate competency. The programs allow for advancement based upon demonstrated achievement of skills and knowledge by the individual apprentice. The traditional term of training may be reduced to not less than onehalf the stated traditional term for the occupation. The program uses curriculum developed by AGC (Associated General Contractors of AmericaNM 2004). The curriculum brings together onthejob experience with classroom training. The AGC of America continues to collaborate with joint and nonjoint contractors, as well as the NCCER, to ensure an eminent training program. The Associated Builders and Contractors. The ABC has approximately eighty chapters nationwide. The formal training programs are registered with the U.S. Department of Labor's Bureau of Apprenticeship and Training (BAT). In 1980, ABC developed a training program called the Wheels of Learning (Associated Builders and Contractors 2004). Since that program, ABC offers the Contren Learning Series, developed by the National Center for Construction Education and Research. This curriculum also includes onthejob training combined with classroom learning. Assessment and Evaluation Assessment tests are given to evaluate or estimate the amount of knowledge and skills an individual possesses on a particular subject. The assessment of an individual is determined by documenting the number of correct answers given by the student. During this literature review, the characterization of assessment tests is best captured by Norton. Norton documents assessment below by quoting other's definitions: According to Hornby (2003), assessment has four main roles: formative, to provide support for future learning; summative, to provide information about performance at the end of a course; certification, selecting by means of qualification; evaluative, a means by which stakeholders can judge the effectiveness of the system as a whole. Such a list is fairly typical but it omits one of the most powerful roles that assessment can have, its effect not only on what students learn but how they learn. Gibbs (1999) has suggested that since students see assessment as the curriculum, effective teaching needs to use this knowledge in order to use the power of assessment strategically to help students learn. Biggs (2002) makes the same point when he says that students learn what they think will be assessed rather than what is in the curriculum. This means that one of the pedagogical benefits of assessment is that it can be used to act as a lever to make students actively engage with a given task. Examinations have traditionally been used for this purpose throughout the entire history of higher education, but the nature of the learning that they engender is frequently passive and nontransformative (Scouller, 1998). Furthermore, as Elton and Johnston (2002, p. 8) point out, examinations tend to test for the lower levels in the hierarchy of knowledge, such as recall and simple applications rather than for creativity, critical thinking or the development of academic and/or life skills (Norton 2004). As described above, assessment can take on multiple connotations. The purpose of assessment is to quantify an individual's knowledge through examinations. As stated above, some students are not retaining the curriculum as a whole; they are only retaining what material they believe will be assessed. It is said that assessments are mostly testing the lower levels of knowledge on a subject; this situation can lead to problems when craftsmen are not passing assessment tests. Craftsmen on the jobsite that are not passing assessment tests which are geared toward lower levels of knowledge in a specific craft can affect the outcome of a productivity and quality of work performed on a jobsite. Most of the assessment tests that are given in the craft related field are multiple choice tests. Questions will be read by the testtaker and then the answer is bubbled onto an answer sheet. Then the answer sheets are read by a computer which interprets the answers on the sheet and returns with a score. With the Contren Learning Series, by NCCER, there are computerized assessment tests. The testtakers read the question on the computer screen and answer the questions on the computer. According to the NCCER, within 15 minutes of receipt of the test answered, results should be available to both Administrator and participant (National Center for Construction Education and Research 2004). Adult Literacy and Education According to the Adult Education and Family Literacy Act in 1998, literacy is an individual's ability to read, write, and speak in English, compute and solve problems, at levels of proficiency necessary to function on the job, in the family of the individual, and in society (National Center for Literacy 1999). Laborer, helper P aint SOp eng eia 18% 'efirk o~aOer 2% 34 Figure 22. Distribution of Construction Workers Who are Racial Minorities (Center to Protect Workers' Rights 2004). In the construction industry, being able to communicate and reading comprehension is vital for a successful jobsite. A large portion of workers are minorities which can lead to a language barrier problem. It is extremely important that workers are safe on a construction project. Figure 22 and 23 are pie charts representing the percentage of racial minorities and Hispanics in the construction industry. Cona iratTc n Imbs reo hrlypr 2304 304.t Figure 23. Distribution of Hispanic Construction Workers (Center to Protect Workers' Rights 2004). Across the United States, about 40 million adults lack a high school credential, and at least six million lack English language skills (National Institute for Literacy 1999). Most of the individuals that fall under the category of illiterate cannot perform tasks that require the simplest literacy and math skills. Most can function at a basic level, but need to improve their skills in order to function more effectively at work, home, and the community (National Institute for Literacy 1999). If individuals working on the j obsite can not understand a substantial amount of English, then they are unable to ask questions or participate in work related discussions. No communication on the jobsite could lead to a large portion of work related injuries. According to the U.S. Bureau of Labor Statistics, construction is one of the most dangerous industries, accounting for a record high of 20.8% of all workplace deaths in 2001 with Latinos as the fastest share of growing share of workforce in the construction industry (New York State Trial Lawyers Association 2004). A large number of workers in the construction industry start their careers in construction immediately after high school. Some workers have dropped out of high school and began their construction career. Illiteracy is not solely restricted to high school dropouts, but it is an issue not to be ignored. Most workers have not received any formal training. Some laborers can learn there job within a few hours, but a journeyman has several years of experience and training. Summary of Literature Review Workers in the construction industry are not required to participate in formal training. Workers learn their skills by apprenticeships, by employee training or by informal on the job training. Different formal training programs are discussed in the literature review. Most of the apprenticeship programs fall under the category of union and nonunion. All the topics covered in this literature review were: * Training Programs: Union and Nonunion * Assessment Test Evaluations * Adult Literacy and Education in Construction In the next chapter of this thesis, the methodology section will be discussed. CHAPTER 3 METHODOLOGY Introduction The purpose of this thesis was to determine if there was a difference between the scores of formally trained individuals and other individuals. The research statistical analysis was performed by using the reported skill assessment data from the Liska Study. The Process The following steps have been taken during this thesis: 1. Acquisition and Review of Data 2. Literature Review 3. Data Analyses 4. Conclusion Acquisition of Data The data from Liska Study was collected in two forms: by paper copy and by computer generated data on CD's. The data provided and used for this research was in the program Microsoft Excel. The data was in thirtyone separate files. In each crafts' Excel file, the data was organized into tables and graphs. In the Liska Study, the tables were displayed by each craft. The categories provided were: All, With Training, Training With NCCER and Years of Experience. Within the categories: All, With Training and With NCCER Training, there were two subcategories: Count and Average Score. The data from the tables were also put into graphs comparing years of experience with the average scores. Each of the separated files reported from the Liska Study were compiled into one file. Compiling the separate files into one file made the data more manageable to statistically analyze. Each craft was keep separate from the next craft by the listing each craft by their name. Literature Review The literature review for this research was performed by using research from the past five years. Topics of this subject were researched using scholarly journals and internet websites relating to craft training. Data Analyses After the reported data was compiled into a single file, the statistical analysis was performed by using the descriptive statistics. Microsoft Excel has a tool called data analysis where the function descriptive statistics was used to aid in this research. This function is able to compute the mean, median, standard error, mode, standard deviation, sample variance, range, minimum, maximum, sum and count of the test scores. This function was used on each craft in all the categories: All, With Training, With NCCER Training, and Without Training. This statistical function in Microsoft Excel became approximately 128 statistical tables. From these tables, graphs were used to visually compute the data. The graphs were created by also using Microsoft Excel's chart tool. Graphs for each of the thirtyone crafts were created comparing: average scores between each category: All, With Training, With NCCER Training, and Without Training; average scores and years of experiences in each category: All, With Training, With NCCER Training, and Without Training; and histograms comparing average scores with frequency and cumulative percentages. All of tables and figures from this thesis are displayed in Appendices A and B and discussed in Chapter 4. To further investigate if there is a significant difference between the assessment test scores of formally trained craftworkers and other workers, the Coefficient of Variation, an Unequal Variance ttest and an Ftest were performed at a 95% confidence level. Hypotheses were formed before the calculations were performed: Ho: There is no statistically significant difference between the assessment test scores of formally trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of formally trained workers and other workers. After a meeting with Diane Greene from NCCER, it was suggested to take out the pipeline disciplines, because the pipeline exams do not require the test taker to pass the entire exam for the categorical skills recognition. Therefore, the following crafts were removed: Corrosion Prevention Field Technician 1 Installation; Corrosion Prevention Field Technician 1 Measurement; Corrosion Prevention Field Technician 2; Corrosion Prevention Field Technician 3; Electricaland Instrumentation Pipeline Technician, Field and Control Center Operations Technician; Gas Maintenance Specialty; Gas Pipeline Specialty; Mechanical Pipeline Technician; and Pipeline Maintenance. After analyzing the data with the pipeline scores removed, there was not a difference in the results: the scores were still higher with trained workers than other workers and there was still a statistically significant difference between the scores of trained workers and other workers in All Trades. Therefore, it was decided to include the pipeline scores in this study. The tables and graphs from these calculations created in Microsoft Excel are found in Appendices A and B. 17 Conclusion In the last chapter of this thesis, the conclusion section will include the summary of results from the analysis conducted on the reported data. Also, recommendations from the findings will be discussed as well as future topics for future research on this topic. The data will be will be discussed in detail in next chapter of this thesis which is the Data and Analysis section. CHAPTER 4 DATA AND ANALYSIS Data Explanation This chapter examines the test scores of formally trained individuals in comparison to other individuals. A statistical analysis was performed by using the reported Liska Study. The research documents thirty different crafts in the construction industry. The Liska Study was a statistical analysis of the average test scores of individuals characterized by trade, training, and years of experience. Listed below are the trades included: * Abnormal Operating Conditions Control Center * Abnormal Operating Conditions Gas * Abnormal Operating Conditions General * Boiler Technician * Boilermaker * Commercial Carpenter * Commercial Electrician * Corrosion Prevention Field Technician 1 Installation * Corrosion Prevention Field Technician 1 Measurement * Corrosion Prevention Field Technician 2 * Corrosion Prevention Field Technician 3 * Electrical and Instrumentation Pipeline Technician * Field and Control Center Operations Technician * Gas Maintenance Specialty * Gas Pipeline Operations * HVAC * Industrial Insulator * Industrial Ironworker * Industrial Maintenance Electrician * Industrial Maintenance Mechanic * Industrial Millwright * Industrial Painter * Industrial Pipefitter * Instrumentation Technician * NonDestructive Testing * Pipeline Maintenance Technician * Scaffold Builder Statistical Familiarity In order to make sure the analysis performed in this thesis is a valid statistical study, the advice from Dr. George Casella from the Department of Statistics and Dr. Robert Stroh from the College of Design, Construction, and Planning at the University of Florida was sought. After discussing the data and the researcher's limited statistical experience, it was decided to summarize the data using tables, graphs and histograms. By analyzing the data in those forms, there would be an adequate amount of information to make conclusions. To test the significant difference among the scores of formally trained craftworkers and other workers, additional statistical tests were performed: the Coefficient of Variation, an Unequal Variance ttest and an Ftest were performed at a 95% confidence level. Using the reported NCCER Training Research data, a statistical analysis known as descriptive statistics, was performed for this research. Brief explanations of some statistical terms used in this research are discussed below: Arithmetic mean. Also known as the average or mean. The average score is computed by summing the scores and dividing by the total number of scores. Median. The middle value in a distribution; an equal number of values are below and above the median value. Mode. The value occurring most frequent in the statistical data. Standard deviation. Measures the variation in the distribution, computed by taking the square root of the variance. Calculated by the taking the square root of squared distances from the mean, then averaging the squared deviations. Standard error. The value where the standard deviation is divided by the square root of the sample size number. Sample variance. Measures the variance of the sample mean. Coefficient of variation. Measures the dispersion of a population. tTest. Measures if there is a statistical significant difference between two populations with the level of confidence varying with the degrees of freedom. Ftest. Measures if there is a statistical significant difference among the variances of two populations with a level of confidence varying with degrees of freedom. In the following sections of this thesis, the data analysis is demonstrated in tables and figures followed by written descriptions of findings. Tables of Statistical Analysis An example of the statistical analysis of the skills assessment test scores by craft is in Table 41. The remainder of the tables for each craft is found in Appendix A. Table 41 is representing the average assessment test scores of the 31 crafts. The categories represented below are: All, With Training, With NCCER Training and Without Training. Looking at the category With Training, the data analysis is in categories followed by a numerical value: * Mean: The average test score of individual's with training is 71.11. * Standard Error: The standard error of the test scores is 0.28. * Median: The median of average test scores is 72.17. * Mode The mode of average test scores is 76.00. * Standard Deviation: The standard deviation of test scores is 10.18. * Sample Variance: The variance of test scores is 103.66 * Range: The range of scores in this data set are 75.00 * Minimum: The minimum average score is 22.00. * Maximum: The maximum average score is 97.00. * Sum The sum of all the average scores is 91,241. * Count: The total number of average scores in the With Training category is 1,283. By understanding one category, comparisons among the other categories can be made. Table 41. All Trades All With Training With NCCER Training Without Training Mean 7055 Mean 7111 Mean 7226 Mean 6948 Standard Error 028 Standard Error 028 Standard Error 0 37 Standard Error 033 Median 71 51 Median 72 17 Median 7382 Median 7060 Mode 6900 Mode 7600 Mode 7700 Mode 5900 Standard Deviation 10 12 Standard Deviation 10 18 Standard Deviation 11 05 Standard Deviation 1096 Sample Vanance 102 38 Sample Variance 10366 Sample Vanance 122 13 Sample Vanance 120 12 Range 76 00 Range 75 00 Range 71 50 Range 79 00 Minlmum 21 00 Minimum 22 00 Mnumum 28 50 Minimum 21 00 Maximum 9700 Maximum 9700 Maximum 100 00 Maximum 100 00 Sum 94538 Sum 91241 Sum 63299 Sum 75592 Count 1340 Count 1283 Count 876 Count 1088 The results from the tables 41 and 42 will be discussed by categories: All, With Training, With NCCER Training and Without Training. Category All: The average test score ranged from the lowest with the Boiler Technician at 53.97 to the highest score the Abnormal Operating Conditions Gas at 85.62. The mean score for all trades in the category All is 70.55. The median score of category All is 71.51, precisely 0.96 points above the average mean score for all trades in the All category. The mode for this category is 69.00. The test scores ranged in this category from the minimum score of 21.00 to the maximum score of 97.00. Category With Training: The average score ranged from the lowest with the Boiler Technician at 55.61 to the highest score in the Abnormal Operating Conditions Gas at 86.36. The mean for all trades in the category With Training is 71.11. The median score of category With Training is 72.17, precisely 1.06 points above the average mean score for all trades in the With Training category. The mode for this category is 76.00. The test scores ranged in this category from the minimum score of 22.00 to the maximum score of 97.00. Category With NCCER Training: The average score ranged from the lowest with the Boiler Technician at 55.84 to the highest score in the Abnormal Operating Conditions Gas at 84.66. The mean for all trades in the category With NCCER Training is 72.26. The median score of category With NCCER Training is 73.82, precisely 1.56 points above the average mean score for all trades in the With NCCER Training category. The mode for this category is 77.00. The test scores ranged in this category from the minimum score of 28.50 to the maximum score of 100.00. Category Without Training: The average score ranged was from the lowest with the Boiler Technician at 51.85 to the highest score in NonDestructive Testing at 85.67. The mean for all trades in the category Without Training is 69.48. The median score of category Without Training is 70.62, precisely 1.14 points above the average mean score for all trades in the With NCCER Training category. The mode for this category is 59.00. The test scores ranged in this category from the minimum score of 21.00 to the maximum score of 100.00. In the Table 42, the means from each of the crafts were compiled into one table to compare the average scores in each category. Table 42. Average Scores by Craft and Categories All With Training Mean Mean Abnormal Operating Conditions Control Center 78 77 79 41 Abnormal Operating Conditions Gas 85 62 86 36 Abnormal Operating Conditions General 79 20 79 72 Boiler Technician 5397 5561 Boilermaker 63 52 65 20 Commercial Carpenter 5826 5901 Commercial Electrician 62 82 63 63 Corrosion Prevention Field Technician 1 Installation 6861 68 99 Corrosion Prevention Field Technician 1 Measurement 61 85 62 14 Corrosion Prevention Field Technician 2 59 77 59 82 Corrosion Prevention Field Technician 3 69 70 68 89 Electrical and Instrumentation Pipeline Technician 70 23 70 82 Field and Control Center Operations Technician 76 23 77 29 Gas Maintenance Specialty 76 42 74 39 Gas Pipeline Operations 7432 7421 HVAC 67 04 67 30 Industrial Carpenter 6981 7080 Industrial Electrician 71 06 71 83 Industrial Insulator 70 50 72 24 Industrial Ironworker 74 92 76 00 Industrial Maintenance Electrician 62 60 63 36 Industrial Maintenance Mechanic 64 26 65 43 Industrial Millwright 69 55 70 56 Industnal Painter 71 14 72 42 Industrial Pipefitter 69 30 69 20 Instrumentation Fitter 7441 75 14 Instrumentation Technician 77 37 77 40 Mechanical Pipeline Technician 74 52 74 98 NonDestructive Testing 75 13 6880 Pipeline Maintenance 7795 78 19 Scaffold Builder 72 48 74 50 With NCCER Training Mean 8304 8466 8136 5584 6640 6205 65 64 7038 5785 65 54 7868 6987 7791 7387 7076 6763 7150 7143 7281 7526 6494 6020 7353 76 18 7040 75 11 7493 7517 5867 7840 75 93 The average test score differences in each category are explored in the following section, Review and Discussion of Data from Average Scores. Review and Discussion of Data from Average Scores Without a methodology section from the Liska Study, it is assumed the categories were formed by vague demographic profiles, as seen in Figure 51. With broad Without Training Mean 7838 8436 7825 51 85 6231 5360 6075 6828 6082 6008 7232 7034 7553 81 30 7661 61 26 6761 6848 6794 7439 6021 5629 6788 6804 6930 7430 7528 7304 8567 7687 7687 demographic profiling questions asked, test takers may have incorrectly filled out the questions. Inaccurately answering the demographic profiling questions may perhaps record an individual's score in an incorrect category. The following figures are graphic representations comparing some of the crafts' average scores among the categories: All, With Training, With NCCER Training, and Without Training. Only a few graphs will be discussed in this section to the show differences between the categories. Examples of highest average scores from each category With NCCER Training, With Training, and Without Training are shown. The other graphs of each craft in this thesis are in Appendix B. The following graphs will represent the differences among the categories, as well as the scattering of the highest average scores among the crafts. Abnormal Operating Conditions Control Center 84.00 83.04 83.00 2 82.00 o c 81.00 80.00 79.41 78.77 S79.00 78.38 > 78.00 77.00 76.00 SAll U With Training E With NCCER Training E Without Training Figure 41. Graph of Abnormal Operating Conditions Control Center Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training. Abnormal Operating Conditions Control Center data results, shown in Figure 41 and Figure B1, of average scores are indicating that With NCCER Training has the highest average score of 83.04, followed in descending order With Training with an average score of 79.41, All with an average score of 78.77 and Without Training with an average score of 78.38. The difference between the highest average score category and the lowest average score category is 4.66 points. With the lowest average score and highest score difference at 4.66, it is assumed the difference among the categories is not larger due to the vague demographic profile used to represent each category reported by the Liska Study. Corrosion Prevention Field Technician 1  Measurement 63.00 62 62.14 61.85 62.00 60.82 2 61.00  0 o 0 60.00 59.00 5. 57.85 o 58.00  ? 57.00 56.00 55.00 All With Training O With NCCER Training 0 Without Training Figure 42. Graph of Corrosion Prevention Field 1 Measurement Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training Corrosion Prevention Field 1 Measurement data results, shown in Figure 42 and Figure B9,of average scores are indicating With Training has the highest average score of 62.14; followed in descending order by All with an average score of 61.85; Without Training with an average score of 60.14 and With NCCER Training with an average score of 57.85. The difference between the leading average score category and the lowest average score category is 4.29 points. When the lowest average score and highest score difference is 4.29, it is again assumed the difference among the categories is not larger due to the vague demographic profile used to represent each category reported by the Liska Study. Gas Maintenance Specialty 82.00 81.30 80.00 U) 0 8 78.00 _O 76.42 76.00 74.39 S74.00 72.00 70.00 SAll U With Training O With NCCER Training O Without Training Figure 43. Graph of Gas Maintenance Specialty Comparing Average Scores Between All, With Training, With NCCER Training, and Without Training Gas Maintenance Specialty data results, shown in Figure 43 and Figure B14, of average scores are indicating Without Training with the highest average score of 81.30; followed in descending order by category All with an average score of 76.42; With Training with an average score of 74.39; and With NCCER Training with an average score of 73.87. The difference between the leading average score category and the lowest average score category is 7.43 points. Without Training having the highest score difference among the previous graphs, it is to be assumed the difference among the categories is not larger due to the inaccurate answering and categorizing of the demographic profile questions. Review of Data for Average Scores with 010 Years of Experience The following figures are some of the craft's graphic representations from the NCCER Training Research comparing the average scores and years of experience only from 010 years among the categories: All, With Training, With NCCER Training, and Without Training. The scores do not indicate a steady improvement with an increase in years of experience, because all the crafts' scores are different among years of experience; therefore the scores are not always improving with experience. Refer to the following figures below for examples of scores are not always improving with experience. The other graphs for each craft in this thesis are in Appendix B. Electrical & Instrumentation Pipeline Technician 1000 90 0 80 0 700 S600 500 400 300 200 100 00 0 1 2 3 4 5 6 7 8 9 10 All 654 658 705 635 748 687 703 693 741 572 670 Sw/Training 600 664 692 665 736 677 716 685 763 565 664 Training w/NCCER 61 7 645 599 670 860 600 765 630 803 520 700 Sw/out Training 687 652 725 510 761 699 684 715 686 590 686 Years of Experience with Average Test Scores 1 All U w/ Training 0 Training w/ NCCER 0 w/out Training Figure 44. Graph of Electrical and Instrumentation Pipeline Technician Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and Without Training Electrical and Instrumentation Pipeline Technician data results, shown in Figure 4 4 and Figure B44, show for this craft the highest test scores for the categories: All with a score of 74.8 at 4 years; With Training with a score of 76.3 at 8 years; With NCCER Training with a score of 86.0 at 4 years; and Without Training with a score of 76.1 at 4 years. The lowest test scores for the categories: All with a score of 57.2 at 9 years; With Training with a score of 56.5 at 9 years; With NCCER Training with a score of 52.0 at 9 years; Without Training with a score of 51.0 at 3 years. Abnormal Operating Conditions General 82 0 80 0 780 760 I 740 720 700 68 0 ... 0 1 2 3 4 5 6 7 8 9 10 All 769 772 778 788 781 794 788 795 792 787 Sw/Training 777 781 786 786 790 795 793 793 791 791 Training w/ NCCER 81 2 787 81 3 802 791 791 82 797 804 801 w/out Training 737 753 754 758 792 756 790 773 802 794 777 Years of Experience with Average Test Scores SAll m w/ Training 0 Training w/ NCCER 0 w/out Training Figure 45. Graph of Abnormal Operating Conditions General Comparing Years of Experience and Average Scores Between All, With Training, With NCCER Training, and Without Training Abnormal Operating Conditions General data results, shown in Figure 45 and Figure B35, show for this craft the highest test scores for the categories: All with a score of 79.5 at 8 years; With Training with a score of 90.3 at 0 years; With NCCER Training with a score of 90.2 at 2 years; and Without Training with a score of 92.0 at 9 years. The lowest test scores for the categories: All with a score of 76.9 at 1 year; With Training with a score of 77.7 at 1 year; With NCCER Training with a score of 78.7 at 2 years; Without Training with a score of 73.7 at 0 years. Histograms The following figures 46 to 410 are Histograms equating the average scores, frequency, and cumulative percentages by the categories: All Crafts Including All Categories, All, With Training, With NCCER Training, and Without Training. In the histogram, the average scores are called "Bin" which is evenly distributed by using the minimum and maximum of the data in an ascending order. Histogram of All Crafts Including All Categories >% 30 120.00% S_ i100.00% S 20 80.00% 3 60.00% Frequency 4"10 1 l 40.00%  Cumulative % 20.00% LL 0 ]L.00% 51 85 54 98 58 12 61 26 64 4067 54 70 67 73 81 76 95 80 09 83 22 More SFrequency 1 2 4 10 11 8 24 15 27 14 3 5 uCumulative % 81% 2 425 651371 225829 03 48 39 60 48 822693 5595 97 100 0 Bin Figure 46. Histogram of All Crafts Including All Categories Comparing Average Scores, Frequency, and Cumulative Percentages of All Crafts Including All Categories. The highest scores in the histogram are at 76.95 with the highest frequency of 27. The plotted histogram of All Crafts Including All Categories, shown in Figure 46, indicates: * Average scores ranging from 0 to 100, .81% of the time the average score was below 51.85 with a frequency of 1. * Average scores ranging from 0 to 100, 2.42% of the time the average score was below 54.98 with a frequency of 2 above the score of 51.85. * Average scores ranging from 0 to 100, 5.65% of the time the average score was below 58.12 with a frequency of 4 above the score of 54.98. * Average scores ranging from 0 to 100, 13.71% of the time the average score was below 61.26 with a frequency of 10 above the score of 58.12. * Average scores ranging from 0 to 100, 22.58% of the time the average score was below 64.40 with a frequency of 11 above the score of 61.26. * Average scores ranging from 0 to 100, 29.03% of the time the average score was below 67.54 with a frequency of 8 above the score of 64.40. * Average scores ranging from 0 to 100, 48.39% of the time the average score was below 70.67 with a frequency of 24 above the score of 67.54. * Average scores ranging from 0 to 100, 60.48% of the time the average score was below 73.81 with a frequency of 15 above the score of 70.67. * Average scores ranging from 0 to 100, 82.26% of the time the average score was below 76.95 with a frequency of 27 above the score of 73.81. * Average scores ranging from 0 to 100, 93.55% of the time the average score was below 80.09 with a frequency of 14 above the score of 76.95. * Average scores ranging from 0 to 100, 95.97% of the time the average score was below 83.22 with a frequency of 3 above the score 80.09. * Average scores ranging from 0 to 100, 100% of the time the average score was below 100 with a frequency of 5 above the score 83.22. Histogram of Category All 15 120.00% S  100.00% S10 80% Frequency 60.00% oI 5 .40.00% Cumulative S 20.00% LLr ~^H ^ ^H ^H ^^ ~~\ U 5397 6030 6663 7296 7929 More Frequency 1 2 5 11 11 1  Cumulative % 323% 968% 25 81% 61 29% 9677% 100 O0 Bin  UU % Figure 47. Histogram of Category All Comparing Average Scores, Frequency, and Cumulative Percentages The highest scores in the Category All are the scores 72.96 and 79.29 both with the highest frequency of 11. The plotted histogram of Category All, shown in Figure 47, show for this craft indicates: 0% * Average scores ranging from 0 to 100, 3.23% of the time the average score was below 53.97 with a frequency of 1. * Average scores ranging from 0 to 100, 9.68% of the time the average score was below 60.30 with a frequency of 2 above the score of 53.97. * Average scores ranging from 0 to 100, 25.81% of the time the average score was below 66.63 with a frequency of 5 above the score of 60.30. * Average scores ranging from 0 to 100, 61.29% of the time the average score was below 72.96 with a frequency of 11 above the score of 66.63. * Average scores ranging from 0 to 100, 96.77% of the time the average score was below 79.29 with a frequency of 11 above the score of 72.96. * Average scores ranging from 0 to 100, 100% of the time the average score was below 100 with a frequency of 1 above the score 79.29. Histogram of Category With Training 120.00% 100.00% 80.00% 60.00% 40.00% 20.00% .00% Frequency  Cumulative % 15 10  5  55 61 61 76 67 91 74 06 80 21 More Frequency 1 2 6 10 11 1  Cumulative % 323% 968% 29 03% 61 29% 96 77% 100 00% Bin Figure 48. Histogram of Category With Training Comparing Average Scores, Frequency, and Cumulative Percentages The highest average scores in the category With Training, shown in Figure 48, are 80.21 with the highest frequency of 11. The plotted histogram of Category With Training show for this craft: * Average scores ranging from 0 to 100, 3.23% of the time the average score was below 55.61 with a frequency of 1. * Average scores ranging from 0 to 100, 9.68% of the time the average score was below 61.76 with a frequency of 2 above the score of 55.61. * Average scores ranging from 0 to 100, 29.03% of the time the average score was below 67.91 with a frequency of 6 above the score of 61.76. * Average scores ranging from 0 to 100, 61.29% of the time the average score was below 74.06 with a frequency of 10 above the score of 67.91. * Average scores ranging from 0 to 100, 96.77% of the time the average score was below 80.21 with a frequency of 11 above the score of 74.06. * Average scores ranging from 0 to 100, 100% of the time the average score was below 100 with a frequency of 1 above the score 80.21. Histogram of Category With NCCER Training 120.00% 100.00% 80.00% 60.00% 40.00% 20.00% .00% 15 10  5B 0 5584 61 60 67 37 7313 78 90 More S Frequency 1 3 5 8 11 3 mCumulative % 323% 1290% 2903% 5484% 9032% 100 00% Bin  Frequency  Cumulative % Figure 49 Histogram of Category With NCCER Training Comparing Average Scores, Frequency, and Cumulative Percentages The highest scores in the category With NCCER Training, shown in Figure 49, are 78.90 with a frequency of 11. The plotted histogram of Category With NCCER Training show: * Average scores ranging from 0 to 100, 3.23% of the time the average score was below 55.84 with a frequency of 1. * Average scores ranging from 0 to 100, 12.90% of the time the average score was below 61.60 with a frequency of 3 above the score of 55.84. * Average scores ranging from 0 to 100, 29.03% of the time the average score was below 67.37 with a frequency of 5 above the score of 61.60. * Average scores ranging from 0 to 100, 54.84% of the time the average score was below 73.13 with a frequency of 8 above the score of 67.37. * Average scores ranging from 0 to 100, 90.32% of the time the average score was below 78.90 with a frequency of 11 above the score of 73.13. * Average scores ranging from 0 to 100, 100% of the time the average score was below 100 with a frequency of 3 above the score 80.21. Histogram of Category Without Training 15 120.00% S100.00% 10 80.00% Frequency 60.00% I" 5 40.00% Cumulative % 20.00% 0 5185 5861 6537 7214 7890 More 00% S Frequency 1 2 6 8 11 3 U Cumulative % 323% 968% 2903% 5484% 9032% 100 00% Bin Figure 410. Histogram of Category Without Training Comparing Average Scores, Frequency, and Cumulative Percentages Category Without Training, shown in Figure 410, had the highest frequency of 11 with an average score of 78.90. The plotted histogram of Category Without Training indicate for this craft: * Average scores ranging from 0 to 100, 3.23% of the time the average score was below 51.85 with a frequency of 1. * Average scores ranging from 0 to 100, 9.68% of the time the average score was below 58.61 with a frequency of 2 above the score of 51.85. * Average scores ranging from 0 to 100, 29.03% of the time the average score was below 65.37 with a frequency of 6 above the score of 58.61. * Average scores ranging from 0 to 100, 54.84% of the time the average score was below 72.14 with a frequency of 8 above the score of 65.37. * Average scores ranging from 0 to 100, 90.32% of the time the average score was below 78.90 with a frequency of 11 above the score of 72.14. * Average scores ranging from 0 to 100, 100% of the time the average score was below 100 with a frequency of 3 above the score 78.90. Additional Statistical Tests Hypotheses were formed before the calculations were performed: Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. To further investigate if there is a significant difference between the assessment test scores of formally trained craftworkers and other workers, the Coefficient of Variation, an Unequal Variance ttest and an Ftest, shown in Appendices A and B, were performed at a 95% confidence level. Abnormal Operating Conditions Control Center 14.00% 12.680o 12.6800 12.00% 11.36c% a 10.0100 9.780 .2 10.00%  ca 8.00% 0 6.00% .' 4.00% 2.00% 0.00% SAll 0 With Training E With NCCER Training E Without Training Figure 411. Graph of Abnormal Operating Conditions Control Center Comparing Coefficient of Variation. After performing a comparison of the Coefficient of Variation, a ttest was performed followed by an Ftest, shown in Table 43 and Table A34. Table 43. Abnormal Operating Conditions Control Center Mean Variance Observations Hypothesized Mean Difference df tStat P(T<t) onetail t Critical onetail P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 79 41 78 38 Mean 101 43 5882 Variance 40 00 38 00 Observations o 00 Hypothesized Mean Difference 7300 df 051 t Stat 031 P(T<t) onetail 1 67 t Critical onetail 061 P(T 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 79 41 78 38 Mean 83 04 78 38 Variance 101 43 5882 Variance 8894 5882 Observations 40 00 38 00 Observations 27 00 38 00 df 3900 37 00 df 2600 37 00 F 1 72 F 151 P(F<=f) onetail o05 P(F<=f) onetail 0 12 F Critical onetail 1 72 F Critical onetail 1 80 In the ttest shown from Table 43, the first table comparing With Training and Without indicates the tStat as 0.51 calculated from the data; P(T<=t) two tail as .61, this is the calculation of probability of the tvalue; and the TCritical two tail at 1.99, which means this is the number the tvalue will need to exceed to be considered significantly difference. By analyzing the table, it can be stated at a 95% confidence level that the scores are not significantly different. In the Ftest shown from Table 43, the first table comparing With Training and Without indicates F as 1.72 which is the variance ratio and the FCritical one tail at 1.72. Without Training 7838 5882 3800 With NCCER 8304 8894 2700 00 4900 212 002 1 68 004 201 By analyzing the table, it can be stated at a 95% confidence level that the variances of assessment test scores are not significantly different. Summary of Data Analysis As stated in the Introduction, the hypotheses were formed regarding the scores of formally trained individuals against other individuals: * Trained craftworkers will have higher assessment scores. * The assessment scores will show a gradual improvement with an increase in the years of experience After this study, the research on exploring the test scores of trained craftworkers compared to other craftworkers demonstrates small differences between the two categories. The trained craftworkers slightly had higher test scores compared to non trained craftworkers. After performing the t and Ftests at a 95% confidence level, it is concluded there is a significant difference between the assessment test scores of formally trained workers compared to other workers in All Trades, shown in Table A52. Not every craft had a significant difference between the average test scores, except for the Scaffold Builder. The Scaffold Builder t and Ftests indicated there was a significant difference between the scores of trained craftworkers and other workers. While the Abnormal Operating ConditionsGas, Commercial Carpenter, Corrosion Prevention Field Technician 1Installation, Electrical and Instrumentation Pipeline Technician, Field and Control Center Operations Technician, HVAC, Industrial Electrician and Industrial Insulator had a significant difference in the variances calculated by the Ftest. The scores did not show a steady improvement with an increase in years of experience, because all the crafts were different among years of experience; the scores are not always improving with an increase in years of experience. The average scores were highest in the category With NCCER Training in 19 out of 31 crafts followed by With Training in 8 out of 31 and Without Training in 4 out of 31 occurrences. It was assumed in the hypotheses Without Training would not have the highest average scores, but as discussed before incorrect recording of the demographic profile questions may have affected the outcome of this data. In 8 out of the 31 crafts, nearly 26 percent of the average scores had a difference greater than the 5.00 points. The smallest margin when comparing the lowest and highest average scores in any category is 0.84 in Instrumentation Fitter shown in Figure B26. The highest margin when comparing the lowest and highest average scores is 27 in Non Destructive Testing shown in Figure B29. The lowest average scores were in the category Without Training in 22 out of 31 crafts followed by With NCCER Training in 5 out of 31 and With Training in 4 out of 31 occurrences. These differences in scores are further detailed in Chapter 5 with conclusions and recommendations. CHAPTER 5 CONCLUSIONS AND RECOMMENDATIONS Synopsis of Research Findings from this research do show trained craftsmen have a slightly higher average on assessment tests than nontrained craftsmen. It should be noted once again that the findings of this study are limited to the reported data from the Liska Study and only applies to the crafts provided from the Liska Study. As stated in the Introduction, hypotheses were formed regarding the scores of formally trained individuals against other individuals and the results are: * Trained craftworkers have higher assessment scores in 27 out of 31 crafts. After performing the t and Ftests at a 95% confidence level, it is concluded there is a significant difference between the assessment test scores of formally trained workers compared to other workers in All Trades. When analyzing each craft, it was concluded not every craft had a statistical significant difference between the average test scores, except for the Scaffold Builder. The Scaffold Builder t and F tests indicated there was a significant difference between the scores of trained craftworkers and other workers. While the Abnormal Operating ConditionsGas, Commercial Carpenter, Corrosion Prevention Field Technician 1Installation, Electrical and Instrumentation Pipeline Technician, Field and Control Center Operations Technician, HVAC, Industrial Electrician and Industrial Insulator had a significant difference in the variances calculated by the Ftest. * The assessment scores comparing years of experience with average scores did not show a gradual improvement with an increase in the years of experience. The lack of consistency indicating an increase of scores with years of experience may have occurred due to vague demographic profile questions asked of test takers. The literature findings indicate trained workers perform at higher productivity rates. The slightly higher average scores are affected by the demographic profile questions asked of the test takers and possibly as discussed in the literature review a language barrier problem with reading and writing in English. Figure A32 shows a graph of all trades comparing the categories: All, With Training, With NCCER Training, and Without Training. In this graph, the difference between the average scores of With Training and Without Training is only 1.63 points. The findings of this research may help in revising the questions on the assessment tests. By changing the demographic profile questions of the test takers, the test score data analysis might show a more accurate representation of the categories. OPTIONAL hi' Curril:z.i.nl i tp Tp= Gender: 0 r,.nii ri1 0 LJr,,',,1 f i% prj'^rrliai 0 Female 0 Amwan ndian Or Alaska fNabi 0 00thFr RiSadial 0 Other 0 UQuid Pipe"im I I .0) 0 0000000 00 00 000 ONo FormalTraining C Gas Piplire 000000 00:, 0000 00000000 OO00000 0000000 00000000 y Wh Ep. aluie: 00000000 0000000 00000000 e Wh0conanuctin 00000000 00000Q0 00*0000 OAscillon OMeinlennc 00000000 0000000 00000000 00000000 0000000 00000000 OLocal OPipeline O0000000 0000000 00000000 OO0000':': 0000000 000000 0 OConfactor 0000000O **eeeO0 00000000 School 3g42 Figure 51. NCCER Assessment Test Questionnaire on Training (National Center for Construction Education and Research Jan. 2004). During the data analysis, some further demographic information would have been helpful in completing this study. Below are some possible questions that should be added to the forms on assessment tests: Formal Training Completed? 0 Yes ONo If Yes, Select all that apply and O NCCER O Union O School O Other: List Years of Training: 0 Less than or equal to 1 02 03 0 4 0 Greater than or equal to 5 Figure 52. Question on Formal Training. The reported data conducted by the Liska Study used the original form in Figure 51 to determine the training category of craftsmen. By adding the question shown in Figure 52, individuals answering the question will have a clearer understanding of the question being asked on formal training. As the question is stated shown in Figure 51, an individual that may not have completed a formal training program may have answered "Yes" on the form in the category of Training, instead of the accurate answer, "No". Not answering the question properly, may affect the average score data outcome of categories between With Training and Without Training by categorizing incorrect average scores in the category. Training Conducted By Whom: O Association 0 Union 0 Contractor O School Figure 53. Question on By Whom. By asking the question shown in Figure 53, future studies on the apprenticeship training programs can be explored. Comparisons of scores can be determined not only by years of experience, but also by the type of apprenticeship program a craftsperson has attended. Experience Type: Check all that apply and Give Years of Experience: O Industrial / Years of Exp. O Commercial / Years of Exp. O Residential / Years of Exp. O Liquid Pipeline / Years of Exp. O Gas Pipeline / Years of Exp. Figure 54. Question on Experience Type. An experience type question in a particular field including the years of experience, as seen in Figure 54, will make possible better demographic information on the working background of the craftsmen taking the assessment test. Education Level: Check highest level completed O High School / GED O Vocational College O 2 year Degree O 4 year Degree O Graduate Degree Figure 55. Question on Education Level. The Figure 55 added to the assessment test forms, will make it possible to categorize the education levels of craftsmen taking fiture assessment tests. Age: 0 1834 0 2530 0 3135 0 3640 0 4150 051> Figure 56. Question on Age. By asking the age of craftsmen taking the assessment test as in Figure 56, it will enhance the demographic categories of scores from the craftsmen involved with the assessment tests. Have you taken this test before? 0 Yes 0 No If Yes, what was your previous score? Figure 57. Question on Have You Taken This Test Before. Figure 57 asks the craftsmen if they have taken this test before. If the craftsmen answers Yes, then their previous score is recorded. This question will help sort out repeat scores, as well as create an additional category on repeat craft assessment test takers. By adding the questions from Figures 51 through 57, future research will more accurately reflect the skills and levels of experiences of craftworkers. Presently, there are two questions on training: on curriculum and by whom. The brief questions asked on the demographics of the test taken might have caused the minor differences in the scores of trained workers versus nontrained workers. For example, if a worker started a formal program, but did not complete the training, that individual still might check the box for training. This would lead to the incorrect score dispersion across the different categories. Recommendations for Future Research While completing this thesis, several areas for future studies were identified: * Examine the scores of craftworkers based on age. * Investigate the scores of craftworkers based on their education and years of experience. * Study the scores of craftworkers based on minority status. * Categorizing the scores of craftsmen by industry. * Research the scores of craftworkers based on location: Northwest, Southwest, Midwest, Southcentral, Northeast, Southeast, Alaska, Hawaii and Puerto Rico. * Investigate the scores of repeat test takers. * Examine the scores of craftsmen based on their affiliations with union or nonunion apprenticeship programs * Perform the same study on training craftsmen compared to other craftsmen, after the prescribed new questions are added to the assessment test forms APPENDIX A TABLES OF STATISTICAL ANALYSIS The tables Ai thru A33 are a statistical analysis of each craft. The data is in categories: All, With Training, With NCCER Training and Without Training. Table A1. Abnormal Operating Conditions Control Center With Training Mean Standard Error Median Mode Standard Deviation Sample Variance Range Minimum Maximum Sum 44 Count With NCCER Training Mean Standard Error Median Mode Standard Deviation Sample Variance Range Minimum Maximum Sum 40 Count Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum 27 Count Table A2. Abnormal Operating Conditions Gas With Training 85 62 Mean 0 82 Standard Error 85 86 Median 84 50 Mode 561 Standard Deviation 31 43 Sample Variance 25 00 Range 72 00 Minimum 97 00 Maximum 4024 Sum With NCCER Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum 44 Count Mean Standard Error Without Training Median Mode Standard Deviation Sample Vanance Range Mi1mmum Maximum Sum Count Without Training ALL Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count 47 Count 12 Count 46 Table A3. Abnormal Operating Conditions General With Training With NCCER Training 79 20 Mean 0 88 Standard Error 80 34 Median Mode 6 74 Standard Deviation 45 38 Sample Vanance 51 50 Range 37 00 Minimum 88 50 Maximum 4594 Sum 58 Count 79 72 Mean 0 88 Standard Error 80 59 Median 80 00 Mode 6 71 Standard Deviation 45 08 Sample Variance 52 67 Range 37 00 Minimum 89 67 Maximum 4624 Sum 58 Count 81 36 Mean 0 96 Standard Error 82 01 Median 88 50 Mode 704 Standard Deviation 49 61 Sample Vanance 52 33 Range 37 00 Minimum 89 33 Maximum 4393 Sum 54 Count Table A4. Boiler Technician With Training 53 97 Mean 1 33 Standard Error 54 62 Median 58 00 Mode 8 64 Standard Deviation 74 74 Sample Vanance 36 44 Range 32 00 Mimnmum 68 44 Maximum 2267 Sum 42 Count Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count With Training 55 84 Mean 2 80 Standard Error 55 44 Median 69 00 Mode 11 89 Standard Deviation 141 44 Sample Vanance 38 00 Range 40 00 Minimum 78 00 Maximum 1005 Sum 18 Count With NCCER Training 63 52 Mean 1 74 Standard Error 65 85 Median 6900 Mode 11 69 Standard Deviation 136 64 Sample Vanance 61 00 Range 2100 Mimnmum 82 00 Maximum 2858 Sum 45 Count 6520 Mean 1 45 Standard Error 65 47 Median 7900 Mode 9 26 Standard Deviation 85 84 Sample Variance 57 00 Range 25 00 Minimum 82 00 Maximum 2673 Sum 41 Count 66 40 Mean 2 14 Standard Error 66 75 Median 80 00 Mode 11 11 Standard Deviation 123 38 Sample Vanance 49 00 Range 35 00 Minimum 8400 Maximum 1793 Sum 27 Count Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Coumt Table A5. Boilermaker Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count Table A6. Commercial Carpenter With Training 58 26 Mean 1 22 Standard Error 58 50 Median 5700 Mode 742 Standard Deviation 55 00 Sample Vanance 30 60 Range 42 40 Mimnmum 73 00 Maximum 2156 Sum 37 Count 5901 Mean 1 23 Standard Error 59 40 Median 6700 Mode 725 Standard Deviation 52 59 Sample Variance 31 08 Range 41 92 Mimmum 73 00 Maximum 2065 Sum 35 Count 62 05 Mean 181 Standard Error 61 50 Median 6100 Mode 809 Standard Deviation 65 49 Sample Vanance 3150 Range 42 00 Mimnmum 73 50 Maximum 1241 Sum 20 Count Table A7. Commercial Electrician With Training 62 82 Mean 1 65 Standard Error 62 50 Median 60 67 Mode 9 74 Standard Deviation 94 78 Sample Vanance 51 50 Range 27 00 Minimum 78 50 Maximum 2199 Sum 35 Count 63 63 Mean 1 78 Standard Error 62 92 Median 60 60 Mode 10 40 Standard Deviation 108 13 Sample Variance 60 00 Range 27 00 Mimmum 87 00 Maximum 2164 Sum 34 Count 65 64 Mean 3 29 Standard Error 68 00 Median 68 00 Mode 1187 Standard Deviation 140 79 Sample Vanance 49 50 Range 35 00 Mimmum 8450 Maximum 853 Sum 13 Count Table A8. Corrosion Prevention Field Technician 1 Installation With Training With NCCER Training Without Training 6861 Mean 0 69 Standard Error 70 46 Median 73 00 Mode 5 09 Standard Deviation 25 86 Sample Vanance 22 70 Range 53 50 Minimum 76 20 Maximum 3705 Sum 54 Count 68 99 Mean 0 76 Standard Error 69 85 Median Mode 5 49 Standard Deviation 30 18 Sample Variance 24 50 Range 53 50 Mimmum 78 00 Maximum 3588 Sum 52 Count 70 38 Mean 0 93 Standard Error 70 35 Median 6450 Mode 6 46 Standard Deviation 41 68 Sample Vanance 33 00 Range 53 00 Minimum 86 00 Maximum 3378 Sum 48 Count With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minmum Maximum Sum Count With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count 48 Table A9. Corrosion Prevention Field Technician 1 Measurement With Training With NCCER Training 61 85 Mean 097 Standard Error 60 92 Median Mode 6 74 Standard Deviation 45 46 Sample Vanance 31 25 Range 51 75 Mimnmum 83 00 Maximum 2969 Sum 48 Count 62 14 Mean 1 06 Standard Error 6125 Median 5667 Mode 729 Standard Deviation 5321 Sample Vanance 35 00 Range 48 00 Minimum 83 00 Maximum 2920 Sum 47 Count 57 85 Mean 1 72 Standard Error 58 05 Median 59 25 Mode 11 18 Standard Deviation 124 95 Sample Vanance 60 50 Range 2850 Mimnium 89 00 Maximum 2430 Sum 42 Count Table A10. Corrosion Prevention Field Technician 2 With Training With NCCER Training 5977 Mean 1 13 Standard Error 5924 Median 50 00 Mode 8 01 Standard Deviation 64 22 Sample Variance 47 00 Range 40 00 Mimmum 87 00 Maximum 2989 Sum 50 Count 59 82 Mean 1 22 Standard Error 59 00 Median 55 00 Mode 851 Standard Deviation 72 50 Sample Vanance 46 33 Range 40 67 Minmmum 87 00 Maximum 2931 Sum 49 Count 6554 Mean 201 Standard Error 67 50 Median 56 00 Mode 12 39 Standard Deviation 153 53 Sample Vanance 56 00 Range 31 00 Mnnimum 87 00 Maximum 2490 Sum 38 Count Table A11. Corrosion Prevention Field Technician 3 With Training With NCCER Training 69 70 Mean 131 Standard Error 6867 Median 69 00 Mode 8 97 Standard Deviation 80 49 Sample Variance 48 00 Range 44 00 Mimmum 92 00 Maximum 3276 Sum 47 Count 68 89 Mean 1 74 Standard Error 6900 Median 63 00 Mode 11 95 Standard Deviation 14277 Sample Variance 68 00 Range 2400 Mimmum 92 00 Maximum 3238 Sum 47 Count 78 68 Mean 1 63 Standard Error 7975 Median 76 00 Mode 9 48 Standard Deviation 89 83 Sample Vanance 40 00 Range 56 00 Mnnimum 96 00 Maximum 2675 Sum 34 Count Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minmum Maximum Sum Count Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count 49 Table A12. Electrical and Instrumentation Pipeline Technician With Training With NCCER Training 70 23 Mean 0 71 Standard Error 70 61 Median 71 00 Mode 481 Standard Deviation 23 12 Sample Vanance 26 50 Range 53 00 Mimnmum 79 50 Maximum 3230 Sum 46 Count 70 82 Mean 0 83 Standard Error 71 00 Median 69 00 Mode 5 58 Standard Deviation 31 12 Sample Variance 30 00 Range 53 00 Mimmum 83 00 Maximum 3187 Sum 45 Count 69 87 Mean 1 35 Standard Error 70 00 Median 7300 Mode 823 Standard Deviation 67 70 Sample Vanance 3400 Range 52 00 Mimnmum 86 00 Maximum 2585 Sum 37 Count Table A13. Field and Control Center Operations Technician With Training With NCCER Training Without Training 76 23 Mean 0 75 Standard Error 76 83 Median Mode 5 11 Standard Deviation 26 10 Sample Vanance 28 00 Range 60 00 Mimnmum 88 00 Maximum 3507 Sum 46 Count 7729 Mean 0 85 Standard Error 7775 Median 78 50 Mode 5 63 Standard Deviation 31 73 Sample Variance 31 00 Range 60 00 Mimmum 91 00 Maximum 3401 Sum 44 Count 7791 Mean 1 15 Standard Error 78 40 Median 85 00 Mode 691 Standard Deviation 47 82 Sample Vanance 2950 Range 60 00 Mimimum 89 50 Maximum 2805 Sum 36 Count Table A14. Gas Maintenance Specialty With Training With NCCER Training 76 42 Mean 1 64 Standard Error 78 67 Median 84 00 Mode 9 41 Standard Deviation 88 63 Sample Vanance 36 00 Range 56 00 Mimimum 92 00 Maximum 2522 Sum 33 Count 7439 Mean 1 68 Standard Error 7493 Median 8400 Mode 8 86 Standard Deviation 78 57 Sample Vanance 36 00 Range 56 00 Minimum 92 00 Maximum 2083 Sum 28 Count 7387 Mean 417 Standard Error 7733 Median 6400 Mode 931 Standard Deviation 86 76 Sample Vanance 2000 Range 6400 Mimnmum 84 00 Maximum 369 Sum 5 Count Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Milnmum Maximum Sum Count Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Mimnmum Maximum Sum Count Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count Table A15. Gas Pipeline Operations With Training 74 32 Mean 1 04 Standard Error 75 00 Median 75 00 Mode 577 Standard Deviation 33 33 Sample Vanance 2277 Range 60 33 Mimnmum 83 10 Maximum 2304 Sum 31 Count 7421 Mean 1 16 Standard Error 75 50 Median 73 00 Mode 6 24 Standard Deviation 38 98 Sample Variance 25 67 Range 60 33 Mimnmum 86 00 Maximum 2152 Sum 29 Count 70 76 Mean 1 56 Standard Error 70 50 Median 7700 Mode 763 Standard Deviation 58 19 Sample Vanance 30 00 Range 56 00 Mimimum 86 00 Maximum 1698 Sum 24 Count Table A16. HVAC 6763 Mean 260 Standard Error 72 00 Median 55 00 Mode 10 08 Standard Deviation 10166 Sample Vanance 29 00 Range 49 00 Minimum 78 00 Maximum 1015 Sum 15 Count Table A17. Industrial Carpenter 6981 Mean 1 06 Standard Error 70 02 Median 72 30 Mode 735 Standard Deviation 54 06 Sample Vanance 31 16 Range 54 18 Mimnmum 85 33 Maximum 3351 Sum 48 Count 70 80 Mean 1 15 Standard Error 70 94 Median 73 85 Mode 769 Standard Deviation 59 10 Sample Variance 33 65 Range 52 35 Mimimum 86 00 Maximum 3186 Sum 45 Count 71 50 Mean 1 42 Standard Error 71 53 Median Mode 8 03 Standard Deviation 64 52 Sample Vanance 3169 Range 5431 Mimnmum 86 00 Maximum 2288 Sum 32 Count With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Milnmum Maximum Sum Count With Training With NCCER Training Without Training All Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count Mean Standard Error Median Mode Standard Deviation Sample Variance Range Minimum Maximum Sum Count Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count With Training With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count Table A18. Industrial Electrician With Training 71 06 Mean 1 03 Standard Error 72 78 Median Mode 723 Standard Deviation 52 21 Sample Vanance 38 68 Range 45 32 Mimimum 84 00 Maximum 3482 Sum 49 Count 71 83 Mean 0 98 Standard Error 7301 Median Mode 6 86 Standard Deviation 47 00 Sample Variance 35 28 Range 48 72 Mimnmum 84 00 Maximum 3519 Sum 49 Count 71 43 Mean 1 25 Standard Error 72 75 Median 72 75 Mode 758 Standard Deviation 57 45 Sample Vanance 3714 Range 46 86 Mimimum 84 00 Maximum 2643 Sum 37 Count Table A19. Industrial Insulator With Training 70 50 Mean 1 42 Standard Error 71 01 Median Mode 9 21 Standard Deviation 84 89 Sample Variance 50 00 Range 40 00 Mimnmum 90 00 Maximum 2961 Sum 42 Count 72 24 Mean 1 38 Standard Error 72 59 Median Mode 884 Standard Deviation 78 20 Sample Vanance 39 50 Range 52 50 Mimmum 92 00 Maximum 2962 Sum 41 Count 7281 Mean 291 Standard Error 75 79 Median 88 80 Mode 1454 Standard Deviation 21135 Sample Vanance 5325 Range 38 00 Minimum 9125 Maximum 1820 Sum 25 Count Table A20. Industrial Ironworker With Training 7492 Mean 1 02 Standard Error 75 92 Median 70 70 Mode 680 Standard Deviation 4621 Sample Vanance 3448 Range 53 30 Minimum 87 78 Maximum 3296 Sum 44 Count 76 00 Mean 0 97 Standard Error 75 98 Median 76 00 Mode 6 22 Standard Deviation 38 71 Sample Variance 30 85 Range 57 00 Mimnmum 87 85 Maximum 3116 Sum 41 Count 7526 Mean 1 32 Standard Error 76 00 Median 76 00 Mode 6 84 Standard Deviation 4677 Sample Vanance 27 57 Range 58 00 Mimnium 85 57 Maximum 2032 Sum 27 Count With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minmum Maximum Sum Count With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count 52 Table A21. Industrial Maintenance Electrician With Training 62 60 Mean 1 06 Standard Error 62 50 Median 65 75 Mode 6 06 Standard Deviation 36 77 Sample Vanance 22 00 Range 52 00 Minimum 74 00 Maximum 2066 Sum 33 Count 63 36 Mean 1 23 Standard Error 64 33 Median 64 00 Mode 6 97 Standard Deviation 48 65 Sample Variance 23 83 Range 50 67 Miimum 74 50 Maximum 2028 Sum 32 Count 6494 Mean 2 71 Standard Error 65 00 Median Mode 766 Standard Deviation 58 60 Sample Vanance 2100 Range 55 00 Mimnmum 76 00 Maximum 520 Sum 8 Count Table A22. Industrial Maintenance Mechanic All With Training With NCCER Training 64 26 Mean 1 17 Standard Error 64 25 Median 71 00 Mode 743 Standard Deviation 55 17 Sample Vanance 35 00 Range 44 00 Minmmum 79 00 Maximum 2571 Sum 40 Count 65 43 Mean 1 15 Standard Error 6492 Median 71 00 Mode 717 Standard Deviation 51 42 Sample Vanance 32 87 Range 52 13 Minimum 85 00 Maximum 2552 Sum 39 Count 60 20 Mean 3 09 Standard Error 61 00 Median 60 00 Mode 11 96 Standard Deviation 143 03 Sample Vanance 41 00 Range 36 00 Minimum 7700 Maximum 903 Sum 15 Count Table A23. Industrial Millwright With Training 69 55 Mean 0 99 Standard Error 69 28 Median Mode 6 92 Standard Deviation 47 87 Sample Vanance 52 00 Range 38 00 Mimnmum 90 00 Maximum 3408 Sum 49 Count 70 56 Mean 0 78 Standard Error 69 96 Median 78 50 Mode 5 40 Standard Deviation 29 20 Sample Variance 30 44 Range 59 56 Miimmum 90 00 Maximum 3387 Sum 48 Count 73 53 Mean 0 95 Standard Error 72 06 Median 7700 Mode 624 Standard Deviation 38 98 Sample Vanance 2900 Range 6100 Minmmum 90 00 Maximum 3162 Sum 43 Count With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Coumt With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count Without Training Table A24. Industrial Painter With Training 71 14 Mean 1 27 Standard Error 71 28 Median 87 50 Mode 8 40 Standard Deviation 7061 Sample Variance 40 50 Range 47 00 Minimum 87 50 Maximum 3130 Sum 44 Count 72 42 Mean 1 34 Standard Error 73 01 Median 87 50 Mode 891 Standard Deviation 79 30 Sample Vanance 4700 Range 47 00 Minimum 94 00 Maximum 3186 Sum 44 Count 76 18 Mean 1 81 Standard Error 76 98 Median 82 00 Mode 10 26 Standard Deviation 105 32 Sample Vanance 41 50 Range 52 50 Minimum 9400 Maximum 2438 Sum 32 Count Table A25. Industrial Pipefitter With Training 69 30 Mean 101 Standard Error 71 18 Median Mode 718 Standard Deviation 51 55 Sample Vanance 38 00 Range 46 00 Minmmum 84 00 Maximum 3534 Sum 51 Count 6920 Mean 1 04 Standard Error 71 04 Median 75 50 Mode 736 Standard Deviation 54 24 Sample Variance 39 00 Range 46 00 Minimum 85 00 Maximum 3460 Sum 50 Count 70 40 Mean 1 25 Standard Error 71 30 Median 68 29 Mode 7 72 Standard Deviation 59 53 Sample Vanance 33 27 Range 50 73 Mimnmum 84 00 Maximum 2675 Sum 38 Count Table A26. Instrumentation Fitter With Training 7441 Mean 1 53 Standard Error 75 90 Median 73 75 Mode 10 15 Standard Deviation 102 95 Sample Vanance 62 40 Range 2200 Mimnmum 84 40 Maximum 3274 Sum 44 Count 75 14 Mean 1 59 Standard Error 76 12 Median Mode 10 17 Standard Deviation 103 39 Sample Vanance 66 00 Range 2200 Mimnmum 88 00 Maximum 3081 Sum 41 Count 75 11 Mean 1 79 Standard Error 71 30 Median 85 00 Mode 8 02 Standard Deviation 64 28 Sample Vanance 27 60 Range 59 40 Minimum 87 00 Maximum 1502 Sum 20 Count With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count Table A27. Instrumentation Technician With Training With NCCER Training 7737 Mean 086 Standard Error 78 81 Median 81 00 Mode 5 70 Standard Deviation 32 45 Sample Vanance 25 14 Range 61 00 Minimum 86 14 Maximum 3404 Sum 44 Count 7740 Mean 0 83 Standard Error 78 34 Median Mode 5 43 Standard Deviation 29 44 Sample Variance 25 00 Range 61 00 Miimum 86 00 Maximum 3328 Sum 43 Count 74 93 Mean 1 52 Standard Error 76 00 Median 7750 Mode 8 45 Standard Deviation 71 40 Sample Vanance 3400 Range 56 00 Minimum 90 00 Maximum 2323 Sum 31 Count Table A28. Mechanical Pipeline Technician With Training With NCCER Training 74 52 Mean 0 65 Standard Error 74 76 Median 80 00 Mode 4 63 Standard Deviation 21 44 Sample Vanance 2427 Range 65 73 Mimnmum 90 00 Maximum 3726 Sum 50 Count 75 13 Mean 5 46 Standard Error 7700 Median 56 00 Mode 1543 Standard Deviation 238 13 Sample Vanance 40 00 Range 56 00 Minimum 96 00 Maximum 601 Sum 8 Count Mean Standard Error Median Mode Standard Deviation Sample Variance Range Miimum Maximum Sum 49 Count 75 17 Mean 1 03 Standard Error 75 00 Median 7400 Mode 6 46 Standard Deviation 41 77 Sample Vanance 27 00 Range 63 00 Mimnmum 90 00 Maximum 2932 Sum 39 Count With NCCER Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count 58 67 Mean 2 67 Standard Error 56 00 Median 56 00 Mode 4 62 Standard Deviation 21 33 Sample Vanance 8 00 Range 56 00 Minimum 64 00 Maximum 176 Sum 3 Count Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count Table A29. NonDestructive Testing All With Training Column Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count Table A30. Pipeline Maintenance Technician With Training With NCCER Training 7795 Mean 0 75 Standard Error 78 68 Median 80 00 Mode 5 92 Standard Deviation 35 06 Sample Vanance 40 50 Range 53 50 Minimum 94 00 Maximum 4833 Sum 62 Count 78 19 Mean 0 58 Standard Error 78 89 Median Mode 4 46 Standard Deviation 19 93 Sample Variance 24 00 Range 66 00 Minimum 90 00 Maximum 4613 Sum 59 Count 78 40 Mean 0 63 Standard Error 79 28 Median Mode 452 Standard Deviation 20 41 Sample Vanance 2286 Range 65 00 Mimnmum 87 86 Maximum 3998 Sum 51 Count Table A31. Scaffold Builder With Training 72 48 Mean 1 00 Standard Error 72 58 Median 70 00 Mode 6 23 Standard Deviation 38 76 Sample Vanance 33 00 Range 56 00 Mimnmum 89 00 Maximum 2827 Sum 39 Count Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count With Training 75 93 Mean 2 19 Standard Error 76 00 Median 88 00 Mode 1094 Standard Deviation 119 75 Sample Vanance 40 73 Range 55 27 Minimum 96 00 Maximum 1898 Sum 25 Count With NCCER Training 70 55 Mean 0 28 Standard Error 71 51 Median 6900 Mode 10 12 Standard Deviation 10238 Sample Variance 76 00 Range 21 00 Minimum 9700 Maximum 94538 Sum 1340 Count 7111 Mean 0 28 Standard Error 72 17 Median 7600 Mode 10 18 Standard Deviation 103 66 Sample Vanance 75 00 Range 22 00 Minimum 9700 Maximum 91241 Sum 1283 Count 72 26 Mean 0 37 Standard Error 73 82 Median 7700 Mode 11 05 Standard Deviation 122 13 Sample Vanance 71 50 Range 28 50 Minimum 10000 Maximum 63299 Sum 876 Count Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count With NCCER Training Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Mimnmum Maximum Sum Coumt Table A32. All Trades Without Training Mean Standard Error Median Mode Standard Deviation Sample Vanance Range Minimum Maximum Sum Count Tables of Average Scores Table A33. Average Scores by Craft and Categories All With Training Abnormal Operating Conditions Control Center Mean 78 77 Mean 79 41 Abnormal Operating Conditions Gas Mean 85 62 Mean 86 36 With NCCER Training Without Training Mean 83 04 Mean 7! Mean 84 66 Mean 8 Abnormal Operating Conditions General Boiler Technician Boilermaker Commercial Carpenter Commercial Electncian Corrosion Prevention Field Technician 1 Installation Corrosion Prevention Field Technician 1 Measurement Corrosion Prevention Field Technician 2 Corrosion Prevention Field Technician 3 Electrical and Instrumentation Pipeline Technician Field and Control Center Operations Technician Gas Maintenance Specialty Gas Pipeline Operations HVAC Industrial Carpenter Industrial Electncian Industrial Insulator Industrial Ironworker Industrial Maintenance Electrician Industrial Maintenance Mechanic Industrial Millwright Industrial Painter Industrial Pipefitter Instrumentation Fitter Instrunentation Technician Mechanical Pipeline Technician NonDestructive Testing Pipeline Maintenance Scaffold Builder Mean 79 20 Mean 79 72 Mean 5397 Mean 5561 Mean 63 52 Mean 65 20 Mean 5826 Mean 5901 Mean 62 82 Mean 63 63 Mean 6861 Mean 6899 Mean 61 85 Mean 62 14 Mean 5977 Mean 5982 Mean 69 70 Mean 68 89 Mean 70 23 Mean 70 82 Mean 7623 Mean 7729 Mean 76 42 Mean 74 39 Mean 7432 Mean 7421 Mean 6704 Mean 6730 Mean 69 81 Mean 70 80 Mean 71 06 Mean 71 83 Mean 70 50 Mean 72 24 Mean 74 92 Mean 76 00 Mean 62 60 Mean 63 36 Mean 64 26 Mean 65 43 Mean 69 55 Mean 70 56 Mean 71 14 Mean 7242 Mean 69 30 Mean 69 20 Mean 7441 Mean 75 14 Mean 7737 Mean 7740 Mean 7452 Mean 7498 Mean 75 13 Mean 6880 Mean 7795 Mean 78 19 Mean 72 48 Mean 74 50 Mean 81 36 Mean Mean 55 84 Mean Mean 66 40 Mean Mean 62 05 Mean Mean 65 64 Mean Mean 70 38 Mean Mean 57 85 Mean Mean 65 54 Mean Mean 78 68 Mean Mean 69 87 Mean Mean 7791 Mean Mean 73 87 Mean Mean 70 76 Mean Mean 67 63 Mean Mean 71 50 Mean Mean 71 43 Mean Mean 7281 Mean Mean 7526 Mean Mean 6494 Mean Mean 6020 Mean Mean 73 53 Mean Mean 76 18 Mean Mean 70 40 Mean Mean 75 11 Mean Mean 7493 Mean Mean 75 17 Mean Mean 58 67 Mean Mean 78 40 Mean Mean 75 93 Mean The tables A34 thru A65 are ttests and FTests of each craft. The tests are comparing the categories: With Training, With NCCER Training and Without Training. 57 Table A34. Abnormal Operating Conditions Control Center: tTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T<t) onetail t Critical onetail P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 79 41 78 38 Mean 101 43 5882 Variance 40 00 38 00 Observations 0 00 Hypothesized Mean Difference 7300 df 051 t Stat 031 P(T<t) onetail 1 67 t Critical onetail 061 P(T 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 79 41 78 38 Mean 83 04 78 38 Variance 101 43 5882 Variance 8894 5882 Observations 40 00 38 00 Observations 27 00 38 00 df 3900 3700 df 2600 3700 F 1 72 F 151 P(F<=f) onetail 005 P(F<=f) onetail 0 12 F Critical onetail 1 72 F Critical onetail 180 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers Without Training 7838 5882 3800 With NCCER 8304 8894 2700 00 4900 212 002 1 68 004 201 58 Table A35. Abnormal Operating Conditions Gas: tTest and FTest tTest: TwoSample Assuming Unequal Variances With Without With Without Training Training NCCER Training Mean 86 36 84 36 Mean 84 66 84 36 Variance 4037 62 46 Variance 263 16 62 46 Observations 44 00 37 00 Observations 12 00 37 00 Hypothesized Mean Difference o oo Hypothesized Mean Difference o 00 df 6900 df 1300 t Stat 124 t Stat 006 P(T P(T FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 86 36 84 36 Mean 84 66 84 36 Variance 4037 62 46 Variance 263 16 62 46 Observations 44 00 37 00 Observations 12 00 37 00 df 4300 3600 df 1100 3600 F 065 F 421 P(F<=f) onetail 0 09 P(F<=f) onetail o00 F Critical onetail 059 F Critical onetail 207 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are significantly different than the score variances of other workers. 59 Table A36. Abnormal Operating Conditions General: tTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T t Critical onetail P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 79 72 78 25 Mean 45 08 35 76 Variance 58 00 55 00 Observations 000 Hypothesized Mean Difference 11100oo df 1 24 t Stat 011 P(T 1 66 t Critical onetail 022 P(T 1 98 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 7972 7825 Mean 81 36 7825 Variance 4508 35 76 Variance 4961 35 76 Observations 58 00 55 00 Observations 54 00 55 00 df 5700 5400 df 5300 5400 F 126 F 139 P(F<=f) onetail 020 P(F<=f) onetail 0 12 F Critical onetail 1 56 F Critical onetail 157 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 7825 3576 5500 With NCCER 8136 4961 5400 000 10400 248 001 1 66 001 1 98 60 Table A37. Boiler Technician: tTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 5561 51 85 Mean 85 75 67 17 Variance 39 00 34 00 Observations 0 00 Hypothesized Mean Difference 71 00 df 184 t Stat 0 03 P(T<t) onetail 1 67 t Critical onetail 0 07 P(T 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 5561 51 85 Mean 5584 5185 Variance 85 75 67 17 Variance 141 44 6717 Observations 3900 3400 Observations 1800 3400 df 3800 3300 df 1700 3300 F 128 F 211 P(F<=f) onetail 0 24 P(F<=f) onetail 0 03 F Critical onetail 1 76 F Critical onetail 1 94 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 5185 6717 3400 With NCCER 5584 141 44 1800 00 2600 1 27 011 1 71 021 206 61 Table A38. Boilermaker: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T<t) onetail t Critical onetail P(T<t) twotail t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 6520 6231 Mean 8584 10005 Variance 41 00 42 00 Observations 0 oo Hypothesized Mean Difference 8100oo df 1 37 t Stat 0 09 P(T<t) onetail 1 66 t Critical onetail 0 18 P(T<t) twotail 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 6520 6231 Mean 6640 6231 Variance 8584 100 05 Variance 12338 10005 Observations 41 00 42 00 Observations 27 00 42 00 df 4000 41 00 df 2600 4100 F 086 F 123 P(F<=f) onetail 0 31 P(F<=f) onetail 0 27 F Critical onetail 059 F Critical onetail 1 77 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 6231 10005 4200 With NCCER 6640 12338 2700 00 51 00 1 55 006 1 68 013 201 62 Table A39. Commercial Carpenter: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T<t) onetail t Critical onetail P(T<t) twotail t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 59 01 53 60 Mean 52 59 92 82 Variance 35 00 26 00 Observations 0 00 Hypothesized Mean Difference 4500 df 240 t Stat S01 P(T<t) onetail 1 68 t Critical onetail 0 02 P(T<t) twotail 201 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 59 01 53 60 Mean 62 05 53 60 Variance 52 59 92 82 Variance 65 49 92 82 Observations 35 00 26 00 Observations 20 00 26 00 df 3400 2500 df 1900 2500 F 057 F 071 P(F<=f) onetail 0 06 P(F<=f) onetail 0 22 F Critical onetail 055 F Critical onetail 047 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are significantly different than the score variances of other workers. Without Training 5360 9282 2600 With NCCER 6205 6549 2000 00 4400 323 000 1 68 000 202 63 Table A40. Commercial Electrician: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 63 63 53 60 Mean 108 13 92 82 Variance 34 00 26 00 Observations 0 00 Hypothesized Mean Difference 5600 df 386 t Stat 000 P(T<t) onetail 1 67 t Critical onetail 000 P(T<t) twotail 2 00 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 63 63 60 75 Mean 65 64 60 75 Variance 108 13 86 13 Variance 140 79 8613 Observations 34 00 22 00 Observations 13 00 22 00 df 3300 2100 df 1200 2100 F 126 F 163 P(F<=f) onetail 030 P(F<=f) onetail 0 16 F Critical onetail 1 99 F Critical onetail 225 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 5360 9282 2600 With NCCER 6564 14079 1300 00 2000 3 17 000 1 72 000 209 64 Table A41. Corrosion Prevention Field Technician 1 Installation: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 68 99 68 28 Mean 30 18 22 02 Variance 52 00 50 00 Observations 000 Hypothesized Mean Difference 9900 df 0 70 t Stat 0 24 P(T 048 P(T 1 98 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 68 99 68 28 Mean 70 38 68 28 Variance 30 18 22 02 Variance 41 68 2202 Observations 52 00 50 00 Observations 48 00 50 00 df 5100 4900 df 4700 4900 F 137 F 189 P(F<=f) onetail 0 13 P(F<=f) onetail o01 F Critical onetail 1 60 F Critical onetail 161 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 6828 2202 5000 With NCCER 7038 4168 4800 000 8600 183 004 1 66 007 1 99 Table A42. Corrosion Prevention Field Technician 1 Measurement: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T t Critical onetail P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 62 14 6082 Mean 5321 70 58 Variance 47 00 43 00 Observations 0 oo Hypothesized Mean Difference 8400 df 0 79 t Stat 0 22 P(T<t) onetail 1 66 t Critical onetail 043 P(T 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 62 14 6082 Mean 57 85 6082 Variance 5321 7058 Variance 12495 7058 Observations 47 00 43 00 Observations 42 00 43 00 df 4600 4200 df 41 00 4200 F 075 F 177 P(F<=f) onetail 0 17 P(F<=f) onetail 003 F Critical onetail 061 F Critical onetail 1 67 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are significantly different than the score variances of other workers. Without Training 6082 7058 43 00 With NCCER 5785 12495 42 00 000 7600 1 38 009 1 67 0 17 1 99 66 Table A43. Corrosion Prevention Field Technician 2: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T<t) onetail t Critical onetail P(T<t) twotail t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 59 82 60 08 Mean 72 50 13063 Variance 49 00 41 00 Observations 000 Hypothesized Mean Difference 7300 df 0 12 t Stat 0 45 P(T<t) onetail 1 67 t Critical onetail 091 P(T<t) twotail 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 59 82 60 08 Mean 65 54 60 08 Variance 72 50 13063 Variance 15353 13063 Observations 49 00 41 00 Observations 38 00 41 00 df 4800 4000 df 3700 4000 F 056 F 118 P(F<=f) onetail 003 P(F<=f) onetail 031 F Critical onetail 061 F Critical onetail 171 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 6008 13063 4100 With NCCER 6554 15353 3800 000 7500 203 002 167 005 1 99 67 Table A44. Corrosion Prevention Field Technician 3: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T<t) onetail t Critical onetail P(T<t) twotail t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 68 89 72 32 Mean 14277 161 08 Variance 47 00 34 00 Observations 000 Hypothesized Mean Difference 6900 df 123 t Stat 0 11 P(T<t) onetail 1 67 t Critical onetail 022 P(T<t) twotail 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 68 89 72 32 Mean 78 8 72 32 Variance 14277 161 08 Variance 8983 161 08 Observations 47 00 34 00 Observations 3400 3400 df 4600 3300 df 3300 3300 F 089 F 056 P(F<=f) onetail 0 35 P(F<=f) onetail 0 05 F Critical onetail 059 F Critical onetail 056 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 7232 16108 3400 With NCCER 7868 8983 3400 000 6100 234 001 167 002 2 00 68 Table A45. Electrical and Instrumentation Pipeline Technician: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 70 82 70 34 Mean 3112 3266 Variance 45 00 43 00 Observations 0 00 Hypothesized Mean Difference 8600 df 040 t Stat 034 P(T<t) onetail 1 66 t Critical onetail 069 P(T 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 70 82 70 34 Mean 69 87 70 34 Variance 3112 32 66 Variance 67 70 32 66 Observations 45 00 43 00 Observations 37 00 43 00 df 4400 4200 df 3600 4200 F 095 F 207 P(F<=f) onetail o 44 P(F<=f) onetail o 01 F Critical onetail 060 F Critical onetail 1 70 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are significantly different than the score variances of other workers. Without Training 7034 3266 43 00 With NCCER 6987 6770 3700 000 6300 0 29 039 1 67 69 Table A46. Field and Control Center Operations Technician: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 77 29 75 53 Mean 3173 1652 Variance 44 00 40 00 Observations 0 00 Hypothesized Mean Difference 7800 df 165 t Stat 005 P(T<t) onetail 1 66 t Critical onetail 0 10 P(T 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 7729 7553 Mean 7791 7553 Variance 31 73 1652 Variance 47 82 1652 Observations 44 00 40 00 Observations 36 00 40 00 df 4300 3900 df 3500 3900 F 192 F 289 P(F<=f) onetail 0 02 P(F<=f) onetail o 00 F Critical onetail 169 F Critical onetail 1 72 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are significantly different than the score variances of other workers. Without Training 7553 1652 40 00 With NCCER 7791 4782 3600 000 5500 1 81 004 1 67 008 200 70 Table A47. Gas Maintenance Specialty: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T<t) onetail t Critical onetail P(T<t) twotail t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 74 39 81 30 Mean 7857 191 50 Variance 28 00 18 00 Observations o 00 Hypothesized Mean Difference 2600 df 188 t Stat 004 P(T<t) onetail 1 71 t Critical onetail 0 07 P(T 2 06 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 7439 8130 Mean 7387 8130 Variance 7857 191 50 Variance 86 76 19150 Observations 2800 1800 Observations 500 1800 df 2700 1700 df 400 1700 F 041 F 045 P(F<=f) onetail o 02 P(F<=f) onetail o 23 F Critical onetail 050 F Critical onetail 0 17 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 8130 19150 1800 With NCCER 7387 8676 500 00 1000 1 40 010 181 019 223 71 Table A48. Gas Pipeline Operations: TTest and FTest tTest: TwoSample Assuming Unequal Variances With Without Training Training Mean Variance Observations Hypothesized Mean Difference df tStat P(T t Critical onetail P(T<t) twotail t Critical twotail 7421 38 98 2900 000 2800 1 15 0 13 1 70 026 205 7661 Mean 48 19 Variance 16 00 Observations Hypothesized Mean Difference df tStat P(T t Critical onetail P(T<t) twotail t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 7421 7661 Mean 70 76 7661 Variance 3898 48 19 Variance 58 19 48 19 Observations 2900 1600 Observations 2400 1600 df 2800 1500 df 2300 1500 F 081 F 121 P(F<=f) onetail o 30 P(F<=f) onetail o 36 F Critical onetail 049 F Critical onetail 2 30 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 7661 48 19 1600 With NCCER 7076 58 19 2400 00 3400 2 51 001 1 69 002 203 Table A49. HVAC: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T t Critical onetail P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 67 30 61 26 Mean 7328 10986 Variance 29 00 15 00 Observations 0 oo Hypothesized Mean Difference 2400 df 1 92 t Stat 003 P(T<t) onetail 1 71 t Critical onetail o 07 P(T 2 06 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 67 30 61 26 Mean 67 63 6126 Variance 7328 10986 Variance 101 66 10986 Observations 2900 1500 Observations 1500 1500 df 2800 1400 df 1400 1400 F 067 F 093 P(F<=f) onetail o 18 P(F<=f) onetail o 44 F Critical onetail 048 F Critical onetail 040 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are significantly different than the score variances of other workers. Without Training 6126 10986 1500 With NCCER 6763 101 66 1500 00 2800 1 70 005 1 70 010 205 73 Table A50. Industrial Carpenter: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T P(T<t) twotail t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 7080 6761 Mean 59 10 62 55 Variance 45 00 43 00 Observations 0 00 Hypothesized Mean Difference 8600 df 1 92 t Stat 0 03 P(T<t) onetail 1 66 t Critical onetail 0 06 P(T 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 7080 6761 Mean 71 50 6761 Variance 59 10 62 55 Variance 64 52 62 55 Observations 45 00 43 00 Observations 32 00 43 00 df 4400 4200 df 31 00 4200 F 094 F 103 P(F<=f) onetail 0 43 P(F<=f) onetail 0 46 F Critical onetail 060 F Critical onetail 1 72 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 6761 6255 4300 With NCCER 71 50 6452 3200 00 6600 209 002 1 67 004 200 74 Table A51. Industrial Electrician: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 71 83 68 48 Mean 47 00 66 62 Variance 49 00 43 00 Observations 0 00 Hypothesized Mean Difference 8200 df 2 12 t Stat 0 02 P(T<t) onetail 1 66 t Critical onetail 004 P(T 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 71 83 68 48 Mean 71 43 68 48 Variance 47 00 66 62 Variance 57 45 66 62 Observations 49 00 43 00 Observations 37 00 43 00 df 4800 4200 df 3600 4200 F 071 F 086 P(F<=f) onetail 0 12 P(F<=f) onetail 0 33 F Critical onetail 061 F Critical onetail o 58 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are significantly different than the score variances of other workers. Without Training 6848 66 62 4300 With NCCER 71 43 5745 3700 00 7800 1 68 005 1 66 010 1 99 Table A52. Industrial Insulator: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T< t) onetail t Critical onetail P(T< t) twotail t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 72 24 67 94 Mean 7820 10447 Variance 41 00 34 00 Observations 0 00 Hypothesized Mean Difference 6600 df 1 93 t Stat 0 03 P(T<t) onetail 1 67 t Critical onetail 006 P(T<t) twotail 2 00 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 7224 67 94 Mean 7281 6794 Variance 7820 10447 Variance 211 35 10447 Observations 41 00 34 00 Observations 25 00 34 00 df 4000 3300 df 2400 3300 F 075 F 202 P(F<=f) onetail 0 19 P(F<=f) onetail 0 03 F Critical onetail 058 F Critical onetail 1 85 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are significantly different than the score variances of other workers. Without Training 6794 10447 3400 With NCCER 7281 211 35 2500 00 41 00 1 44 008 1 68 016 202 76 Table A53. Industrial Ironworker: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 76 00 74 39 Mean 38 71 44 76 Variance 41 00 37 00 Observations 0 00 Hypothesized Mean Difference 7400 df 1 10 t Stat 0 14 P(T<t) onetail 1 67 t Critical onetail 028 P(T 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 76 00 74 39 Mean 75 26 74 39 Variance 38 71 44 76 Variance 46 77 44 76 Observations 41 00 37 00 Observations 27 00 37 00 df 4000 3600 df 2600 3600 F 086 F 104 P(F<=f) onetail 0 33 P(F<=f) onetail 0 44 F Critical onetail 058 F Critical onetail 181 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 7439 4476 3700 With NCCER 7526 4677 2700 00 5500 051 031 1 67 061 200 77 Table A54. Industrial Maintenance Electrician: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T<t) onetail t Critical onetail P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 63 36 60 21 Mean 4865 51 98 Variance 32 00 23 00 Observations o 00 Hypothesized Mean Difference 4700 df 162 t Stat 0 06 P(T<t) onetail 1 68 t Critical onetail 011 P(T 201 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 6336 6021 Mean 6494 6021 Variance 4865 51 98 Variance 5860 51 98 Observations 32 00 23 00 Observations 8 00 23 00 df 3100 2200 df 700 2200 F 094 F 113 P(F<=f) onetail 0 43 P(F<=f) onetail 0 38 F Critical onetail 0 53 F Critical onetail 2 46 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 6021 51 98 2300 With NCCER 6494 5860 800 000 1200 1 53 008 1 78 0 15 2 18 78 Table A55. Industrial Maintenance Mechanic: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T<t) onetail t Critical onetail P(T<t) twotail t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 65 43 56 29 Mean 51 42 4863 Variance 39 00 23 00 Observations 0 00 Hypothesized Mean Difference 4700 df 493 t Stat 000 P(T<t) onetail 1 68 t Critical onetail 000 P(T<t) twotail 201 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 65 43 56 29 Mean 60 20 56 29 Variance 51 42 4863 Variance 14303 4863 Observations 39 00 23 00 Observations 15 00 23 00 df 3800 2200 df 1400 2200 F 106 F 294 P(F<=f) onetail 0 46 P(F<=f) onetail o 01 F Critical onetail 1 95 F Critical onetail 2 17 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 5629 48 63 2300 With NCCER 6020 14303 1500 000 2000 1 14 0 13 1 72 027 209 79 Table A56. Industrial Millwright: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T<t) onetail t Critical onetail P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 70 56 67 88 Mean 29 20 52 59 Variance 48 00 44 00 Observations 0 00 Hypothesized Mean Difference 7900 df 200 t Stat 002 P(T<t) onetail 1 66 t Critical onetail 005 P(T<t) twotail 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 70 56 67 88 Mean 73 53 67 88 Variance 29 20 52 59 Variance 38 98 52 59 Observations 48 00 44 00 Observations 43 00 44 00 df 4700 4300 df 4200 4300 F 056 F 074 P(F<=f) onetail 002 P(F<=f) onetail 0 17 F Critical onetail 061 F Critical onetail 060 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 6788 5259 4400 With NCCER 7353 3898 43 00 00 8400 390 000 1 66 000 1 99 80 Table A57. Industrial Painter: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T P(T t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 72 42 68 04 Mean 7930 10361 Variance 44 00 33 00 Observations 0 00 Hypothesized Mean Difference 6400 df 1 97 t Stat 0 03 P(T<t) onetail 1 67 t Critical onetail 005 P(T 2 00 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 7242 6804 Mean 76 18 6804 Variance 7930 10361 Variance 105 32 10361 Observations 44 00 33 00 Observations 32 00 33 00 df 4300 3200 df 31 00 3200 F 077 F 102 P(F<=f) onetail 0 20 P(F<=f) onetail 0 48 F Critical onetail 058 F Critical onetail 181 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 6804 10361 3300 With NCCER 76 18 10532 3200 00 6300 321 000 1 67 000 200 81 Table A58. Industrial Pipefitter: TTest and FTest Mean Variance Observations Hypothesized Mean Difference df tStat P(T< t) onetail t Critical onetail P(T< t) twotail t Critical twotail tTest: TwoSample Assuming Unequal Variances With Without Training Training 69 20 69 30 Mean 54 24 47 71 Variance 50 oo 44 00 Observations 0 oo Hypothesized Mean Difference 9200 df o 07 t Stat 0 47 P(T< t) onetail 1 66 t Critical onetail 094 P(T<t) twotail 1 99 t Critical twotail FTest TwoSample for Variances With Without With Without Training Training NCCER Training Mean 69 20 69 30 Mean 70 40 69 30 Variance 54 24 47 71 Variance 59 53 4771 Observations so oo 44 00 Observations 38 00 44 00 df 4900 4300 df 37 00 4300 F 1 14 F 1 25 P(F<=f) onetail 0 34 P(F<=f) onetail 0 24 F Critical onetail 1 64 F Critical onetail 1 69 Ho: There is no statistically significant difference between the assessment test scores of trained workers and other workers. HA: There is a statistically significant difference between the assessment test scores of trained workers and other workers. TTest. At a 95% confidence level, the assessment test scores of trained workers are not significantly different than the scores of other workers. FTest. At a 95% confidence level, the assessment test score variances of trained workers are not significantly different than the score variances of other workers. Without Training 6930 4771 4400 With NCCER 70 40 5953 3800 00 7500 068 025 1 67 050 1 99 