BUS308 Week 4 Discussion 3 Excel Details

Hello Class,

This week’s assignment was probably the best one so far in the course. I enjoyed working through the correlation and regression test to ultimately come across strong evidence to answer the questions of whether males and females receive equal pay for equal work. After working through the salary variable in the assignment and seeing some of the results in the compa-ratio from the lecture, I decided to use the performance rating to see if there was a correlation in the variables that may be important in answering the key question. Looking at my correlation table, I can see that Service and Age have a correlation (0.565), just like Service and Salary (0.449), Service and Midpoint (0.471), Service and Raise (0.102). The t-value is set to 2.011 and r= 0.278.

Performance Rating

Age

Service

Salary

Midpoint

Raise

Performance Rating

1

Age

0.139238

1

Service

0.225701

0.565133

1

Salary

0.161885

0.537871

0.449622

1

Midpoint

0.191751

0.567111

0.471147

0.988405

1

Raise

0.67366

-0.18043

0.102787

-0.05682

-0.02891

1

Then we are able to see the significant variables correlated to service as age, salary, and midpoint.

The r square tells us that 53% of the variation in performance rating values can be explained by the shared variation in the variable used in analysis. Our Significance F of 2.02E-05 makes us reject our null hypothesis.

After running the test and identifying the data in the regression output, we can then take each variable to identify which one is significant. Looking at the table below, we can see that Service and Raise are of significant in the Performance rate but do not answer the question of whether males and females receive equal pay for equal work. Gender is non significant in how the company does performance rating which is good on that note.

Sorry for the long post. I felt like sharing the data was important instead of just talking about it.