Emotional exhaustion, or burnout, is a significant problem for people with careers in the field of human services. Regression analysis was used to investigate the relationship between burnout and aspects of the human services professional's job and job-related behavior (Journal of Applied Behavioral Science, Vol. 22, 1986). Emotional exhaustion was measured with the Maslach Burnout Inventory, a questionnaire. One of the independent variables considered, called concentration, was the proportion of social contacts with individuals who belong to a person's work group. The next table lists the values of the emotional exhaustion index (higher values indicate greater exhaustion) and concentration for a sample of 25 human services professionals who work in a large public hospital. A Minitab printout of the simple linear regression is provided below.

a. Construct a scatter plot for the data. Do the variables x and y appear to be related?
b. Find the correlation coefficient for the data and interpret its value. Does your conclusion mean that concentration causes emotional exhaustion? Explain.
c. Test the usefulness of the straight-line relationship with concentration for predicting burnout. Use α = .05.
d. Find the coefficient of determination for the model and interpret it.
e. Find a 95% confidence interval for the slope β1. Interpret the result.
f. Use a 95% confidence interval to estimate the mean exhaustion level for all professionals who have 80% of their social contacts within their work groups. Interpret the interval.

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啝 83 79 75 81 75 77 77 85 96 49 89 52 60 85 70 79 71 68 14 40 Id 20 60 38 88 79 87 68 12 35 70 80 92 77 100 $25 300 980 $10 900 400 996 120 son 0 o o o 601006 The regression equation is EXHAUST =-29 + 8.87 CONC EN Constant2 CONCEN -29.5 106.7 -0.28 0.785 8.865 1.471 6.03 0.000 S 174 . 207 R-Sq 61.29 R-Sq (adj ) -59.5% - " inalysis of Variance Source Regression Residual Error 23 698009 Total DF 1 1102408 1102408 36.33 .000 30348 24 1800417 Predicted Values for New Observations Neu Obs Fit SE Fit 95% CI 95% PI 1 679.7 38.7 (599.7, 759.8) (310.6, 1048.9) Values of Predictors tor New Observations Nev Obs CONCEN 80.0