Dear Mr. Banker We have analyzed your banking data to look for signs of gender discrimination at your workplace. You have expressed the belief that all people are created equal regardless of sexual preference, and this analysis will show you whether that attitude is reflected in the salaries of your employees. Finding differences between the males and Females at the bank could help you to notice discrimination even when it may not be intentional. We have used the program R to do regression with the categorical variable gender included. An α level of 0.05 was used to determine significance. As you can see in the residual plot below there are no patterns observed after the regression was used which confirms that our analysis was complete and appropriate for the data. With p-values well below the alpha we can say that men have a higher predicted income at the bank. Their prediction equation is $8.57K/year above the females. Even more disturbing is the fact that the salary increases more per year for the men than it does for the women. It increases and extra $0.39K/year (or $390/year). The prediction equation for people at your bank is Salary = 29.86+8.57*Male+2.53*years+0.39*Male*years Where Male = 0 when using if for a female and 1 when using it for Males. The prediction equations are: For women: Salary = 29.86+2.53*(years of service) For men: Salary = 38.43+2.92*(years of service) This relationship is shown below: As you can see above, the red line is for men and the black line is for women. The salaries for men are higher than for women and the line for men is more steeply slanted upwards for men. This suggests that men are being paid more and they are receiving more compensation for their time with the company. In conclusion we cannot say for certain that gender discrimination is occurring, but there are several facts which are suspicious, and should spur further investigation. Why are men paid more, and why are they receiving higher promotions than the women? Future studies should include the type of job for each person, their age and abilities, as well as the quality of their work at the company. If the women are just as valuable to the company as the men, then this data suggests you need to pay the women more in order to continue to claim that your company does not discriminate based on gender.
Dear Mr. Banker We have analyzed your banking data to look for signs of gender discrimination at your workplace. You have expressed the belief that all people are created equal regardless of sexual preference, and this analysis will show you whether that attitude is reflected in the salaries of your employees. Finding differences between the males and Females at the bank could help you to notice discrimination even when it may not be intentional. We have used the program R to do regression with the categorical variable gender included. An α level of 0.05 was used to determine significance. As you can see in the residual plot below there are no patterns observed after the regression was used which confirms that our analysis was complete and appropriate for the data. With p-values well below the alpha we can say that men have a higher predicted income at the bank. Their prediction equation is $8.57K/year above the females. Even more disturbing is the fact that the salary increases more per year for the men than it does for the women. It increases and extra $0.39K/year (or $390/year). The prediction equation for people at your bank is Salary = 29.86+8.57*Male+2.53*years+0.39*Male*years Where Male = 0 when using if for a female and 1 when using it for Males. The prediction equations are: For women: Salary = 29.86+2.53*(years of service) For men: Salary = 38.43+2.92*(years of service) This relationship is shown below: As you can see above, the red line is for men and the black line is for women. The salaries for men are higher than for women and the line for men is more steeply slanted upwards for men. This suggests that men are being paid more and they are receiving more compensation for their time with the company. In conclusion we cannot say for certain that gender discrimination is occurring, but there are several facts which are suspicious, and should spur further investigation. Why are men paid more, and why are they receiving higher promotions than the women? Future studies should include the type of job for each person, their age and abilities, as well as the quality of their work at the company. If the women are just as valuable to the company as the men, then this data suggests you need to pay the women more in order to continue to claim that your company does not discriminate based on gender.
full%20two%20categories%20regression.docx