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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

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

  • Assuming that these conditions are satisfied, which of the following statements is accurate?
  • 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.
  • 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.
  • Neitheroftheabove.

You have answered this previously saying that B is correct. How did you come to this conclusion? Please explain step by step how this is determined. Thank you!

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