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A colleague is conducting research on adults' job satisfaction as it relates to gender, salary, and level of control felt over the work environment. Your colleague has collected data from a random sample of adults. Salary is measured in thousands of dollars. The control over one's work environment and job satisfaction scales are measured by averaging sets of items on a 0 to 7 point scale range, with low scores representing low control and low job satisfaction and higher scores representing a greater sense of control and job satisfaction.

A colleague is conducting research on adults' job satisfaction as it relates to gender, salary, and level of control felt over the work environment. Your colleague has collected data from a random sample of adults. Salary is measured in thousands of dollars. The control over one's work environment and job satisfaction scales are measured by averaging sets of items on a 0 to 7 point scale range, with low scores representing low control and low job satisfaction and higher scores representing a greater sense of control and job satisfaction.

Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter2: Equations And Inequalities
Section2.1: Equations
Problem 58E
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A colleague is conducting research on adults' job satisfaction as it relates to gender, salary, and level of control felt over the work environment. Your colleague has collected data from a random sample of adults. Salary is measured in thousands of dollars. The control over one's work environment and job satisfaction scales are measured by averaging sets of items on a 0 to 7 point scale range, with low scores representing low control and low job satisfaction and higher scores representing a greater sense of control and job satisfaction. Here are the data. Gender Salary Control Job Satisfaction M 42 4 F 50 2 F 60 5 5 F 40 3 1 M 50 3 2 M 40 7 3 She is particularly interested in the relationship between job satisfaction and the person's perceived level of control. She ran two regressions on the data, both of which are presented below.
Transcribed Image Text:A colleague is conducting research on adults' job satisfaction as it relates to gender, salary, and level of control felt over the work environment. Your colleague has collected data from a random sample of adults. Salary is measured in thousands of dollars. The control over one's work environment and job satisfaction scales are measured by averaging sets of items on a 0 to 7 point scale range, with low scores representing low control and low job satisfaction and higher scores representing a greater sense of control and job satisfaction. Here are the data. Gender Salary Control Job Satisfaction M 42 4 F 50 2 F 60 5 5 F 40 3 1 M 50 3 2 M 40 7 3 She is particularly interested in the relationship between job satisfaction and the person's perceived level of control. She ran two regressions on the data, both of which are presented below.
Output 1 SUMMARY OUTPUT Regression Stoatistics Multiple R 0.676024239 R Square 0.457008771 Adjusted R Square -0.357478071 Standard Eror 19495996 Observations 6 ANOVA Significonce F 0.691050993 df SS MS Regression 3 6.3981228 2,1327076 0.56110025 Residual 2 7.6018772 3.8009386 Total 14 Coefficients Stondard Eror tStat P-votue Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -2779429018 6.087490533 0.456580426 0.6927641 -28.97178678 23.41292874 -28.97178678 23.41292874 Gender -0.806804849 1.900567068 -0.424507434 0.71250097 -8.984284934 7.370675235 -8.984284934 7.370675235 Salary 0.114000782 0.121921434 0.935034786 0.448478468 -0.41058481 0.638586374 0.41058481 0.638586374 Control 0.407899883 0.53423295 0.763524369 0.524923808 -1.890719014 270651879 -1.890719014 2706518779 Output 2 SUMMARY OUTPUT Regression Statistics Multiple R 0,467707173 RSquare 0.21875 Adjusted R Square 0.0234375 Standard Error 1653594569 Observations 6 ANOVA df Significonce F SS MS F Regression Residual 1. 3.0625 3.0625 112 0.349594712 4 10.9375 2734375 Total 14 Coefficients Stondard Error 1.786086271 tStat P-vatue Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.25 0.699954212 0.522582076 -3.708970484 6.208970484 -3.708970484 6.208970484 Control 0.4375 0.413398642 1058300524 0.349594712 -0.710278637 1.585278637 -0.710278637 1.585278637 Using the regression model that is appropriate for predicting job satisfaction using perceived level of control, how much of the variance in job satisfaction is not explained by this regression model? 46.8% 21.9% 53.2% 78.1%
Transcribed Image Text:Output 1 SUMMARY OUTPUT Regression Stoatistics Multiple R 0.676024239 R Square 0.457008771 Adjusted R Square -0.357478071 Standard Eror 19495996 Observations 6 ANOVA Significonce F 0.691050993 df SS MS Regression 3 6.3981228 2,1327076 0.56110025 Residual 2 7.6018772 3.8009386 Total 14 Coefficients Stondard Eror tStat P-votue Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -2779429018 6.087490533 0.456580426 0.6927641 -28.97178678 23.41292874 -28.97178678 23.41292874 Gender -0.806804849 1.900567068 -0.424507434 0.71250097 -8.984284934 7.370675235 -8.984284934 7.370675235 Salary 0.114000782 0.121921434 0.935034786 0.448478468 -0.41058481 0.638586374 0.41058481 0.638586374 Control 0.407899883 0.53423295 0.763524369 0.524923808 -1.890719014 270651879 -1.890719014 2706518779 Output 2 SUMMARY OUTPUT Regression Statistics Multiple R 0,467707173 RSquare 0.21875 Adjusted R Square 0.0234375 Standard Error 1653594569 Observations 6 ANOVA df Significonce F SS MS F Regression Residual 1. 3.0625 3.0625 112 0.349594712 4 10.9375 2734375 Total 14 Coefficients Stondard Error 1.786086271 tStat P-vatue Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.25 0.699954212 0.522582076 -3.708970484 6.208970484 -3.708970484 6.208970484 Control 0.4375 0.413398642 1058300524 0.349594712 -0.710278637 1.585278637 -0.710278637 1.585278637 Using the regression model that is appropriate for predicting job satisfaction using perceived level of control, how much of the variance in job satisfaction is not explained by this regression model? 46.8% 21.9% 53.2% 78.1%
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