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 VIF
Constant -203.402 51.6573 -3.94 0.0002 0.0
Gmat 0.39412 0.09039 4.36 0.0000 2.0
Tuition 0.92012 0.17875 5.15 0.0000 2.0
R-Squared 0.6857 Resid. Mean Square (MSE) 427.511
Adjusted R-Squared 0.6769 Standard Deviation 20.6763
Source DF SS MS F P
Regression 2 67140.9 33570.5 78.53 0.0000
Residual 72 30780.8 427.5
Total 74 97921.7
Interpret the coefficient of determination value shown in the printout.
◦ We expect most of the average starting salaries to fall within $20,676 of their least squares predicted values.
◦ We can explain 68.57% of the variation in the average starting salaries around their mean using the model that includes the average GMAT score and the tuition for the MBA program.
◦ We expect most of the average starting salaries to fall within $41,353 of their least squares predicted values.
◦ At α = 0.05, there is insufficient evidence to indicate that something in the regression model is useful for predicting the average starting salary of the graduates of an MBA program.
starting
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