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Regression analysis: education and salary

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Use the dataset "Employee data" (attached). Perform a regression that studies the impact of years of education on current salary.

1.(a) How may we interpret the coefficient for education?
(b) Is the coefficient for education significant at the 5% level?
(C ) What hypotheses are being tested by the t-statistic?
(d) What percent of variation in current salary does this model explain?
(e) Where did you get that percentage from?

Using the same dataset, now study the impact of education, beginning salary, months since hire and previous experience on current salary.

(2)
(a) Do all these independent variables together have an impact on the dependent variable? How do you know?
(b) Comparing the variables, which independent variable has the largest impact on the dependent variable? Why do you say so?
(c )How may we interpret the coefficient for education?
(d)Why do you think it is a smaller effect than in (1)?
(e) What percent of variation in current salary does this model explain?
(f) Where did you get that percentage from?

Using the same dataset, now study the impact of education, beginning salary, months since hire, previous experience and employee code on salary.

(3)
(a) Does the employee code have a significant impact on current salary?
(b) Would we expect it to? Why or why not?
(C ) Has the adjusted R2 changed since the regression in (2)? Why or why not?

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This solution provides explanations and answers to statistical questions about regression analysis.

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