Model Summary Absent R R Square Adjusted R Square 54 29 26 Anova Absent Sum Of Squares Df 311 51 4 771 88 89 1083 1 (434.15 KiB) Viewed 26 times
Suppose you decide to examine the link between absenteeism andunion-management relations using multiple regression analysis. Theanalysis uses firm-level data. Y = Average # of days absent withina firm in a year Bad_UM_Rel = a dummy variable indicating BADunion-management relations (omitted category = NEUTRAL relations)Good_UM_Rel = a dummy variable indicating GOOD union-managementrelations (omitted category = NEUTRAL relations) Pct_PT = thepercentage of a firm's employees who are part time. Pct_U = thepercentage of a firm's employees who are members of a labor union.Questions: Answer parts (a), (b), (c), (d), (e), and (f). (a) Typethe value of the (unstandardized) slope coefficient on PCT_PT andinterpret its meaning in words. (3 points) (b) Using the p-valuemethod, do a hypothesis test for whether there is a statisticallysignificant relationship between Pct_PT (X3) and Absences (Y). Showall steps to your hypothesis test and use a significance level of5%. (4 points) (c) Type the value of the (standardized) slopecoefficient on PCT_U and interpret its meaning in words. (3 points)(d) Using the p-value method, do a hypothesis test for whetherthere is a statistically significant relationship between Pct_U andAbsences (Y). Show all steps to your hypothesis test and use asignificance level of 5%. (4 points) (e) Type the value of theR-square and interpret its meaning in words. (4 points)
Model Summary (Absent) R R Square Adjusted R Square :54 .29 .26 ANOVA (Absent) Sum of Squares df 311.51 4 771.88 89 1083.39 93 Regression Residual Total Coefficients (Absent) (Constant) Bad_UM_Rel Good_UM_Rel Pct_PT Pct U 4.25 2.11 Std. Error of the Estimate 2.94 Unstandardized Coefficients B Std. Error -.22 -.11 .06 Mean Square F Sig. 77.88 8.98 .000 8.67 .88 .68 .92 .04 .02 Standardized Coefficients Beta t Sig. .00 4.81 .000 .29 3.10 .003 -.02 -.24 .812 -.27 -2.98 .004 .34 3.72 .000
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