Engineering faces a serious gender-based retention problem. Despite all the efforts encouraging women to study engineering,...

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Engineering faces a serious gender-based retention problem. Despite all the efforts encouraging women to study engineering, over 40% of highly skilled women who enter the field end up leaving. Much has been written about why women in the field leave, but we wanted to understand better what encourages some women to stay. In 2014 we interviewed 34 women engineers in two FTSE 100 firms in the UK. Ten of the engineers were in the early stages of their careers, 19 were mid-career, and five were in late career. Over 80% had undergraduate degrees, and 43% had children. The two companies they worked for were PET and TTD (both pseudonyms). PET supplies fuel, energy, lubricants, and petrochemicals, while TTD is one of the world's leading gas and diesel engines suppliers. PET's engineering workforce was about 12% women, and TTD's was about 9%. Both have intransigently masculine cultures but have been committed to increasing their numbers of women engineers. They have tried various initiatives, such as gender-based quota systems for senior posts, flexible work options, and female employee groups. Despite these efforts, senior managers and Human Resource officers in both companies reported that one in three women engineers continued to leave. After conducting a preliminary literature review, the Human Capital Managers of PET and TTD discovers that the leading causes of women engineers leaving include five practices of Human Resource Management (HRM): 1) Employment Security (ES) 2) Selective hiring of new personnel (SH) 3) Self-managed teams and decentralization of decision making (SM) 4) Fair and performance-based compensation (FC) 5) Training in relevant skills (TR) The above practices of HRM have been presented in the attached excel sheet along with data on women engineer's turnover (WET). Furthermore, based on these practices, the Human Capital Managers of PET and TTD advanced the following hypotheses: H1: Employment security will be negatively related to women engineer's turnover at both PET and TTD. H2: Selective hiring of new personnel will be negatively related to female engineers' turnover at PET and TTD. H3: Self-managed teams and decentralization of decision-making will negatively relate to women engineers' turnover at both PET and TTD. H4: Fair and performance-based compensation will be negatively related to female engineers' turnover at PET and TTD. H5: Training in relevant skills will be negatively related to women engineers' turnover at PET and TTD. Required: 1. Using any software of your choice, perform a preliminary analysis to ensure that the basic assumptions of linear regression have been satisfied before conducting your main analysis. 2. Prepare a comprehensive report based on your results to confirm whether the hypotheses formulated by Human Capital Managers of PET and TTD are supported or not. 3. Based on your results, discuss the limitations of your work, and then offer some recommendations to the management of PET and TTD on addressing the issue of women engineer's turnover. Results Linear Regression Model Fit Measures Model 1 Intercept ES SH SM FC TR R Model Coefficients - WET Predictor Estimate 0.849 ES SH SM FC TR Assumption Checks Collinearity Statistics VIF R² 2.15 2.01 1.50 1.30 1.20 0.721 SE 1.04e-4 0.0317 0.00327 -0.1331 0.0465 -2.86396 -0.2988 0.0450 -6.64579 0.8745 0.0389 22.50409 0.0779 0.0362 2.15365 0.032 0.0739 0.0347 2.12917 0.034 Tolerance 0.465 0.497 0.665 0.768 0.835 F 143 [3] t Overall Model Test df1 df2 5 P 0.997 0.005 < .001 < .001 278 p <.001 Engineering faces a serious gender-based retention problem. Despite all the efforts encouraging women to study engineering, over 40% of highly skilled women who enter the field end up leaving. Much has been written about why women in the field leave, but we wanted to understand better what encourages some women to stay. In 2014 we interviewed 34 women engineers in two FTSE 100 firms in the UK. Ten of the engineers were in the early stages of their careers, 19 were mid-career, and five were in late career. Over 80% had undergraduate degrees, and 43% had children. The two companies they worked for were PET and TTD (both pseudonyms). PET supplies fuel, energy, lubricants, and petrochemicals, while TTD is one of the world's leading gas and diesel engines suppliers. PET's engineering workforce was about 12% women, and TTD's was about 9%. Both have intransigently masculine cultures but have been committed to increasing their numbers of women engineers. They have tried various initiatives, such as gender-based quota systems for senior posts, flexible work options, and female employee groups. Despite these efforts, senior managers and Human Resource officers in both companies reported that one in three women engineers continued to leave. After conducting a preliminary literature review, the Human Capital Managers of PET and TTD discovers that the leading causes of women engineers leaving include five practices of Human Resource Management (HRM): 1) Employment Security (ES) 2) Selective hiring of new personnel (SH) 3) Self-managed teams and decentralization of decision making (SM) 4) Fair and performance-based compensation (FC) 5) Training in relevant skills (TR) The above practices of HRM have been presented in the attached excel sheet along with data on women engineer's turnover (WET). Furthermore, based on these practices, the Human Capital Managers of PET and TTD advanced the following hypotheses: H1: Employment security will be negatively related to women engineer's turnover at both PET and TTD. H2: Selective hiring of new personnel will be negatively related to female engineers' turnover at PET and TTD. H3: Self-managed teams and decentralization of decision-making will negatively relate to women engineers' turnover at both PET and TTD. H4: Fair and performance-based compensation will be negatively related to female engineers' turnover at PET and TTD. H5: Training in relevant skills will be negatively related to women engineers' turnover at PET and TTD. Required: 1. Using any software of your choice, perform a preliminary analysis to ensure that the basic assumptions of linear regression have been satisfied before conducting your main analysis. 2. Prepare a comprehensive report based on your results to confirm whether the hypotheses formulated by Human Capital Managers of PET and TTD are supported or not. 3. Based on your results, discuss the limitations of your work, and then offer some recommendations to the management of PET and TTD on addressing the issue of women engineer's turnover. Results Linear Regression Model Fit Measures Model 1 Intercept ES SH SM FC TR R Model Coefficients - WET Predictor Estimate 0.849 ES SH SM FC TR Assumption Checks Collinearity Statistics VIF R² 2.15 2.01 1.50 1.30 1.20 0.721 SE 1.04e-4 0.0317 0.00327 -0.1331 0.0465 -2.86396 -0.2988 0.0450 -6.64579 0.8745 0.0389 22.50409 0.0779 0.0362 2.15365 0.032 0.0739 0.0347 2.12917 0.034 Tolerance 0.465 0.497 0.665 0.768 0.835 F 143 [3] t Overall Model Test df1 df2 5 P 0.997 0.005 < .001 < .001 278 p <.001

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Based on the provided data and analysis lets delve into each aspect of the report and answer the questions elaborately Preliminary Analysis and Assumption Checks Before conducting the main analysis us... View the full answer