Mike Wilde is president of the teachers' union for Otsego School District. In preparing for upcoming negotiations, he would like to investigate the salary structure of classroom teachers in the district. He believes there are three factors that affect a teacher's salary: years of experience, a rating of teaching effectiveness given by the principal, and whether the teacher has a master's degree. A random sample of 20 teachers resulted in the following data. e. The analysis has been rerun without "verbal" and "math." See the following output. Compute the coefficient of determination. How much has changed from the previous analysis? R2

Salary ($ thousands), Y
Years of Experience, X1
Principal's Rating, X2
Master's Degree,*X3

21.1 8 35 0
23.6 5 43 0
19.3 2 51 1
33.0 15 60 1
28.6 11 73 0
35.0 14 80 1
32.0 9 76 0
26.8 7 54 1
38.6 22 55 1
21.7 3 90 1
15.7 1 30 0
20.6 5 44 0
41.8 23 84 1
36.7 17 76 0
28.4 12 68 1
23.6 14 25 0
31.8 8 90 0
20.7 4 62 0
22.8 2 80 1
32.8 8 72 0

Develop a correlation matrix. Which independent variable has the strongest correlation with the dependent variable? Does it appear there will be any problems with multicollinearity?
b. Determine the regression equation. What salary would you estimate for a teacher with five years' experience, a rating by the principal of 60, and no master's degree?
c. Conduct a global test of hypothesis to determine whether any of the regression coefficients differ from zero. Use the .05 significance level.
d. Conduct a test of hypothesis for the individual regression coefficients. Would you consider deleting any of the independent variables? Use the .05 significance level.
e. If your conclusion in part (d) was to delete one or more independent variables, run the analysis again without those variables.