A study of the top MBA programs attempted to predict the average starting salary (in $1000's) of graduates of the program based on the amount of tuition (in $1000's) charged by the program and the average GMAT score of the program's students. The results of a regression analysis based on a sample of 75 MBA programs is shown below:
Least Squares Linear Regression of Salary
Predictor
Variables Coefficient Std Error T P
Constant -687.851 165.406 4.16 0.0001
Tuition -11.3197 2.19724 -5.15 0.0000
GMAT -0.96727 0.25535 -3.79 0.0003
TxG 0.01850 0.00331 5.58 0.0000
R-Squared 0.7816 Resid. Mean Square (MSE) 301.251
Adjusted R-Squared 0.7723 Standard Deviation 17.3566
Source DF SS MS F P
Regression 3 76523.8 25510.9 84.68 0.0000
Residual 71 21388.8 301.3
Total 74 97921.7
Cases Included 75 Missing Cases 0
One of the t-test test statistics is shown on the printout to be the value t = 5.58. Interpret this value.
◦ There is sufficient evidence, at α = 0.05, to indicate that the interaction between average tuition and average GMAT score is a useful predictor of the average starting salary of graduates of MBA programs.
◦ There is sufficient evidence, at α = 0.05, to indicate that at least one of the variables proposed in the interaction model is useful at predicting the average starting salary of graduates of MBA programs.
◦ There is insufficient evidence, at α = 0.05, to indicate that at least one of the variables proposed in the interaction model is useful at predicting the average starting salary of graduates of MBA programs.
◦ There is insufficient evidence, at α = 0.05, to indicate that the interaction between average tuition and average GMAT score is a useful predictor of the average starting salary of graduates of MBA programs.
Model of a sequential study in which two cohorts were followed beginning at age 20. One cohort was f
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