A human resource analyst would like to study the primary factors influencing the base salaries of employees in Germany. He begins by using the age (in years) of the employees to predict the base yearly salary (in €). The file GermanEmployees contains this data for 250 employees who have been at their current workplace for more than a year.

a. Assuming a linear relationship, use the least-squares method to compute the regression coefficients b0 and b1.

b. Interpret the meaning of the Y intercept, b0, and the slope, b1, in this problem.

c. Predict the mean base salary of employees who are 40 years old.

d. Compute the coefficient of determination, r2, and interpret its meaning.

e. Perform a residual analysis and evaluate the regression assumptions.

f. At the 0.05 level of significance, is there evidence of a linear relationship between age and base salary?

g. Construct a 95% confidence interval estimate of the mean base salary of employees who are 35 years old.

h. Construct a 95% prediction interval of the base salary of an individual employee who is 35 years old.

i. Construct a 95% confidence interval estimate of the population slope.

j. What other independent variables might you consider for inclusion in the model? Think of the variables in the dataset or beyond that.

k. What conclusions can you reach concerning the relationship between age and base salary in Germany?