Correct interpretation for regression coefficient of age

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Reference no: EM13148825

A large pharmaceutical company selected a random sample of new hires and obtained their job performance ratings based on their first six months with the company. These data were used to build a multiple regression model to predict the job performance of new hires based on age and GPA. The results of the analysis are shown below. Regression Analysis: Job Performance versus Age, GPA The regression equation is
Job Performance = - 89.7 + 6.18 Age + 2.40 GPA

Predictor Coef, SE Coef, T, P
Constant -89.65 26.29 -3.41 0.002
Age 6.178 1.390 4.45 0.000
GPA 2.395 2.928 0.82 0.420
S = 6.88760 R-Sq = 64.6% R-Sq(adj) = 62.0%
Analysis of Variance
Source DF SS MS F P
Regression 2 2335.4 1167.7 24.62 0.000
Residual Error 27 1280.9 47.4
Total 29 3616.3

Which of the following is the correct interpretation for the regression coefficient of Age?

A) The regression coefficient is not significantly different from zero.
B) For a new hire with a given GPA, an increase in one year of age is associated with a decrease of 6.18 points for job performance on average.
C) The regression coefficient indicates that the job performance score for an older new hire will, on average, be 6.18 times higher than for a younger new hire.
D) The regression coefficient indicates that the job performance score for an older new hire will, on average, be 6.18 times lower than for a younger new hire.
E) For a new hire with a given GPA, an increase in one year of age is associated with an increase of 6.18 points for job performance on average.

Reference no: EM13148825

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