Batch 10:

Data has been gathered to explain executive salaries from a variety of factors.

What is the Multiple Regression to predict SALARY from EXPerience, EDUCation, GENDER, NUMberSupported and ASSETS.

NOTE: Do not forget to include GENDER in the Multiple Regression analysis.

a. What is the regression equation? Write an interpretation of the regression equation for each of the independent variables.

b. What is the coefficient of determination and interpret its value.

c. What is the hypotheses to test for the significance of the independent factors. Using t-tests, at alpha= 0.05 determine which factors are significantly related to Executive SALARY

d. Does the equation meetthe Model Assumptions. How did you determine this?

e. Does this model have multi-collinearity issues? How did you determine this?

f. If you were to recommend a new model , what would it be and why.

Excel Datasheet Link (Copy and Paste into new browser - at pull-down choices, choose "Paste and Go."):

https://1drv.ms/x/s!AgBqCw3o5WRbhPlCcHEzczTBNhNYlg?e=c0Lskf