College basketball is big business, with coaches' salaries, revenues, and expenses in millions of dollars. The data in the file Colleges-basketball (attached) contains the coaches' salaries and revenues for college basketball at selected schools in a recent year (data extracted from R. Adams, "Pay for Playoffs,"The Wall Street Journal, March 11-12, 2006, pp. P1, P8). You plan to develop a regression model to predict a coach's salary based on revenue.
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) Use the prediction line developed in (a) to predict the coach's salary for a school that has revenue of $7 million.
D) Compute the coefficient of determination, r2, and interpret its meaning.
E) Perform a residual analysis on your results and evaluate the regression assumptions.
F) At the 0.05 level of significance, is there evidence of a linear relationship between the coach's salary and revenue?
G) Construct a 95% confidence interval estimate of the population slope.
A linear relationship using the least-squares methods to compute the regression coefficients are determined.