Regression Analysis: Avg. Tot. Score versus Avg. Salary, %Takers Model Summary S
ID: 3155747 • Letter: R
Question
Regression Analysis: Avg. Tot. Score versus Avg. Salary, %Takers
Model Summary
S R-sq R-sq(adj) R-sq(pred)
33.6877 80.56% 79.73% 78.08%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 987.9 31.9 30.99 0.000
Avg. Salary 2.18 1.03 2.12 0.039 1.61
%Takers -2.779 0.228 -12.16 0.000 1.61
Prediction for Avg. Tot. Score
Variable Setting
Avg. Salary 40
%Takers 50
1. Under what conditions are the confidence and prediction intervals computed above valid?
2. Assuming that these conditions are satisfied, which of the following statements is accurate?
A) We are 95% confident that a state with an average teacher salary of $40,000 and 50% of eligible students taking the SAT will have an average total SAT score between 923.418 and 948.945.
B) We are 95% confident that a state with an average teacher salary of $40,000 and 50% of eligible students taking the SAT will have an average total SAT score between 867.219 and 1005.14.
C) Neither of the above.
Please Explain
Explanation / Answer
1. Here the p-values for constant is 0.00 , for avg salary is 0.039 and for % takers is 0.00 all are < 0.05
also the R2 = 80.56 %, R2 adj = 79.73% and R2 pred = 78.08 % all > 70 % or high
assuming that the data is coming from normal population.
So the confidence and prediction intervals computed above valid
2. The given information is not sufficient to answer this part.
Based on only this information we can't figure out the confidence interval.
may be answer is c)