Below is a regression analysis for salary being predicted/explained by the other variables in our sample
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Below is a regression analysis for salary being predicted/explained by the other variables in our sample

2. Below is a regression analysis for salary being predicted/explained by the other variables in our sample (Midpoint, age, performance rating, service,  gender, and degree variables. (Note: since salary and compa are different ways of expressing an employee’s salary, we do not want to have both used in the same regression.)

Ho: The regression equation is not significant.

Ha: The regression equation is significant.

Ho: The regression coefficient for each variable is not significant

Ha: The regression coefficient for each variable is significant

Sal
SUMMARY OUTPUT
  
Multiple R 0.9915591
R Square 0.9831894
Adjusted R Square 0.9808437
Standard Error 2.6575926
Observations 50
ANOVA
  df SS MS F Significance F
Regression 6 17762.3 2960.38 419.1516111 1.812E-36
Residual 43 303.7003 7.0628
Total 49 18066      
  Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept -1.749621 3.618368 -0.4835 0.63116649 -9.046755 5.547512618 -9.04675504 5.54751262
Midpoint 1.2167011 0.031902 38.1383 8.66416E-35 1.1523638 1.281038273 1.152363828 1.28103827
Age -0.004628 0.065197 -0.071 0.943738987 -0.136111 0.126854699 -0.13611072 0.1268547
Performace Rating -0.056596 0.034495 -1.6407 0.108153182 -0.126162 0.012969494 -0.12616237 0.01296949
Service -0.0425 0.084337 -0.5039 0.616879352 -0.212582 0.127581377 -0.21258209 0.12758138
Gender 2.4203372 0.860844 2.81159 0.007396619 0.6842792 4.156395232 0.684279192 4.15639523
Degree 0.2755334 0.799802 0.3445 0.732148119 -1.337422 1.888488483 -1.33742165 1.88848848
Note: since Gender and Degree are expressed as 0 and 1, they are considered dummy variables and can be used in a multiple regression equation.

Interpretation:
For the Regression as a whole:
What is the value of the F statistic: 
What is the p-value associated with this value: 
Is the p-value <0.05?
Do you reject or not reject the null hypothesis: 
What does this decision mean for our equal pay question: 

For each of the coefficients:
What is the coefficient's p-value for each of the variables: 
Is the p-value < 0.05?
Do you reject or not reject each null hypothesis: 
What are the coefficients for the significant variables?
Using only the significant variables, what is the equation?
Is gender a significant factor in salary:
If so, who gets paid more with all other things being equal?
How do we know?
Hint
Statistics419.15161111.81215E-36yesreject Hoas the gender changes from male to female, salary increases by 2.552 units. And performance rating and service have a slightly negative imapct on salary.thus, equal pay for equal work somewhat does not hold here....
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