An academic advisor wants to predict the typical starting salary ofa graduate at

Question

An academic advisor wants to predict the typical starting salary ofa graduate at a top business school using the GMAT score of the school as predictor variable. A simple linear regression of SALARY versus GMAT using 25 data points is shown below. no =-92040 1-228 s= 3213 r2-.66 .81 df= 23 t-6.67 For the situation above, write the equation of the least squares line. A) SALARY = 228 + 92040 (GMAT) B) GMAT = 228-92040 (SALARY) C) GMAT =-92040 + 228 (SALARY) D) SALARY =-92040 + 228 (GMAT) A) We can predict SALARY correctly 81% of the time using GMAT B) We estimate SALARY to increase 81% of the time using GMAT C) There appears to be positive correlation between SALARY D) 81% of the sample variation in SALARY can be explained by For the situation above, give a practical interpretation of r-8I in a straight-line model. in a straight-line model. and GMAT using GMAT in a straight-line model. For the situation above, give a practical interpretation of s-3213 A) We estimate SALARY to increase $3,213 for every 1-point 8) Our predicted value of SALARY will equal 2(3213)-$6,426 for C) We expect to predict SALARY to within 2(3213)-$6,426 of its D) We expect the predicted SALARY to deviate from actual increase in GMAT. any value of GMAT true vale using GMAT in a straight-line mode SALARY by at least 2(3213) $6,426 using GMAT in a straight- line model.

Explanation / Answer

Equation of least square regression line:

SALARY = - 92040 + 228 (GMAT)

Option D is correct.

Practical interpretation of r = 0.81: Option C is correct.

Practical interpretation of s = 3213: Option C is correct.

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