The Principal of an elementary school wanted to predict the percentage of students who would pass a sixth-grade proficiency test. She believes that the passing rate is related to the average teacher salary (in thousands of dollars) and instructional spending per pupil (in thousands of dollars). She collects data on 47 schools throughout the state, enters the data into Excel, and runs a multiple regression analysis. Following are the partial tables:
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.4276
R Square
0.1828
Adjusted R Square
0.1457
Standard Error
5.7351
Observations
47
Coeff
Std Error
T Stat
P-value
Intercept
-72.9916
45.9106
-1.5899
0.1190
Salary
2.7939
0.8974
3.1133
0.0032
Spending
0.3742
0.9782
0.3825
0.7039
Which of the following is a correct statement?
Group of answer choices
18.28% of the total variation in the percentage of students passing the proficiency test can be explained by instructional spending per pupil holding constant the effect of mean teacher salary.
18.28% of the total variation in the percentage of students passing the proficiency test can be explained by mean teacher salary and instructional spending per pupil after adjusting for the number of predictors and sample size.
18.28% of the total variation in the percentage of students passing the proficiency test can be explained by mean teacher salary and instructional spending per pupil.
18.28% of the total variation in the percentage of students passing the proficiency test can be explained by mean teacher salary holding constant the effect of instructional spending per pupil.