Question

14 points Problem 4 A sociologist is studying the relationship between absenteeism among city employees during the year and their relative "job pride" as measured by an index. She has obtained the following data, where high job pride values ostensibly indicate a great deal of job pride Days Absent "Job Pride" İndex | 63 | 82 | 59 | 73 184-167 | 81 | 73 | 63 | 81 | 90 Using SAS (hand calculations only when necessary). Obtain a regression equation (line of best fit) for predicting days absent from the a) b) Plot the data on a scatterplot and draw the regression line. Does it appear to fit the c) index. data well? Estimate the number of days absent if the 'job pride" index is 94 variables at 0.05 with the conclusion from part d d) Calculate rand determine whether there is a linear relationship between the e) Test whether the slope of the regression line is zero and compare your conclusion f Obtain the residual plot. Do any assumptions appear to be violated?

Answer 1

Insert Page Layout Formulas Data Review Home View Cut a Copy Σ AutoSum Format Painter | B 1 u FMerg& Center " Conditional Format Cell Insert Delete Format Sort & Find & Filter Select- Q Clear Font lignment Number Cells G22 1 SUMMARY OUTPUT INDEX Residual Plot StatisticS 4 Multiple R 5 R Square 6 Adjusted R Square 7 Standard Error 8 Observations 0.475872352 0.226454496 0.140504995 3.059523159 10 20 40 6100 2 -10 10 ANOVA INDEX df Significance F MS 124.66295327 24.66295 94 0.138997367 9 84.24613764 9.360682 12 Regression 13 Residual 14 Total 15 16 17 Intercept 18 INDEX 10 108.9090909 coefficients standard Error tstat P-value tower 95% Upper 95% ower 95 O9pper 95.0% 17.35674157 7.112647402 2.440265 0.037348424 1.266815306 33.44667 1.266815 33.44667 0.15431882 0.095071446 1.62319 0.138997367-0.369385373 0.060748 0.36939 0.060748 13927267 UTPUT Residuals Predicted Days ion 7.634655899 0.365344101 25 · ィ·»: Sheett l sheet4. Sheet2 Sheet3タ Ready ENG IN O Type here to search enov

Date Page (syrで序3C-6-15 ( index) 0ア 104P . 644 pvalus 0300 나.ile