Homework Clinic
Mathematics Clinic => Statistics => Topic started by: Jramos095 on Jan 16, 2020
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Each year a nationally recognized publication conducts its "Survey of America's Best Graduate and Professional Schools." An academic advisor 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.
b0 = -92040 b1 = 228 s = 3213 R2 = 0.66 r = 0.81 df = 23 t = 6.67
Give a practical interpretation of R2 = 0.66.
◦ 66% of the differences in SALARY are caused by differences in GMAT scores.
◦ 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.
◦ We can predict SALARY correctly 66% of the time using GMAT in a straight-line model.
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66% of the sample variation in SALARY can be explained by using GMAT in a straight-line model.
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Thank you
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Thank You.