A Study of the Top MBA Programs Attempted to Predict $\mathrm { F } = 84.68$

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

Cases Included 75 Missing Cases 0
The global-f test statistic is shown on the printout to be the value $\mathrm { F } = 84.68$ . Interpret this value.
A) There is sufficient evidence, at $\alpha = 0.05$ , 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.
B) There is instufficient evidence, at $\alpha = 0.05$ , 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.
C) There is sufficient evidence, at $\alpha = 0.05$ , 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.
D) There is insufficient evidence, at $\alpha = 0.05$ , 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.