Suppose 3 researcher gathered survey d3t3 from 19 employees and 3sked the employ

Question

Suppose 3 researcher gathered survey d3t3 from 19 employees and 3sked the employees to rate their job satisfaction on a scale from 0 to 100 (with 100 being perfectly satisfied). Suppose the following d3t3 represent the results of this survey. Assume th3t relationship with supervisor is rated on a scale from 0 to 50 (0 represents a poor relationship and 50 represents an excellent relationship); overall quality of the work environment is rated on 3 scale from 0 to 100 (0 represents poor work environment and 100 rep resents an excellent work environment); and opportunities for advancement 2 is rated on 3 scale from 0 to 50 (0 represents no opportunities and 50 represents excellent opportunities). Answer the following questions: Wh3t is the regression formula? How reliable do you think the estimates will be based on this formula? Explain your answer by citing the relevant metrics. Are there any variables th3t do not appear to be good predictors of job satisfaction? How can you tell? If 3 new employee reports th3t her rel3tionship with her supervisor is 40. rates her opportunities for advancement to be 3t 30. finds the quality of the work environment to be 3t 75. and works 60 hours per week, what would you expect her job satisfaction score to be?

Explanation / Answer

The regression equation is given by JS = 1.39(RS) + 0.32(OA) - 0.04(OQ) -0.09(TH) -1.47

The R2 value is 0.9616 i.e., only 96.16% of the variability in Job Satisfaction is explained by this model.

c) The variable RS( relationship with Supervisor) is not a good predictor in this case

d) with the given informatoion the Job Score will be 56.8

SUMMARY OUTPUT Regression Statistics Multiple R 0.980643687 R Square 0.961662041 Adjusted R Square 0.950708339 Standard Error 5.141304649 Observations 19 ANOVA df SS MS F Significance F Regression 4 9282.56939 2320.642347 87.79333267 9.41183E-10 Residual 14 370.062189 26.4330135 Total 18 9652.631579 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -1.469115885 8.116129341 -0.181011887 0.858952586 -18.87648205 15.93825028 -18.87648205 15.93825028 RS 1.390775797 0.260762575 5.333494651 0.000105561 0.831495698 1.950055895 0.831495698 1.950055895 OA 0.317368664 0.116142397 2.732582347 0.016189046 0.068267997 0.566469331 0.068267997 0.566469331 OQ 0.043295651 0.121230504 0.357134957 0.726316766 -0.216717919 0.303309221 -0.216717919 0.303309221 TH -0.09445984 0.102220838 -0.924076163 0.37110035 -0.313701732 0.124782053 -0.313701732 0.124782053

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