Refer to the attached excel file, answer the questions below. Use graph if required.

The file that can be accessed through the link below contains data on 100 employees in a particular occupation. Suppose that interest centres on investigating the factors that explain salary differences. The data set contains the following variables.

·        Salary: individual salary measured in thousands of dollars

·        Education: individual education level measured in years of schooling

·        Experience: individual work experience measured in years of employment

·        Male: gender dummy variable with the value 1 for male and 0 for female

Q1. Attach scatterplots of Salary against Education and Salary against Experience. Describe their associations based on the scatterplots.

Q2. Construct a multiple regression model that explain salary differences. Attach your regression output. Write down your estimated model.

Q3. What is the R²? What does it mean?

Q4. What is the estimated intercept? How do you interpret it?

Q5. What is the marginal effect of education on salary? Is it statistically significant?

Q6. Are any explanatory variables statistically insignificant in explaining Salary? Discuss your reasoning from hypothesis testing.

Q7. Predict a female worker salary whose education and experience levels equal to average education and experience levels in the sample.

Q8. Attach the residual plot against the predicted salary. What do you observe on the residual plot?