Question

Each year a nationally recognized publication conducts its "Survey of America's Best Graduate and
Professional Schools."
An academic adviser wants to predict the typical starting salary of a graduate at a top business
school using GMAT score of the school as a predictor variable. A simple linear regression of
SALARY versus GMAT using 25 data points shown below.
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b0 = -92040 b1 = 228 s = 3213 R2 = .66 r = .81 df = 23 t = 6.67

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Give a practical interpretation of  R 2= .66.

Group of answer choices

We expect to predict SALARY to within 2 0.66 = $1,620 of its true value using GMAT in a straight-line model

We can predict SALARY correctly 66% of the time using GMAT in a straight-line model.

66% of the sample variation in SALARY can be explained by using GMAT in a straight-line model.

We estimate SALARY to increase $.66 for every 1-point increase in GMAT.

Answer 1

Answer: 66% of the sample variation in SALARY can be explained by using GMAT in a straight-line model.

Explanation: In the linear regression mode R2 value is 0.66. It means 66% of the sample variation in SALARY can be explained by using GMAT in a straight-line model.