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Introduction In order to check the relationship between benefits and the intrinsic, extrinsic and total job satisfaction, 3 bivariate regressions are run. Using the regression equations the linear relationship between the independent variable (benefit) and the 3 sets of dependent variables (total job satisfaction, intrinsic job satisfaction and extrinsic job satisfaction) is established. Bivariate regression analysis shows how the explanatory power of the independent variable in determining the values of the dependent variable (Malhotra, 543).
The results from the regression analysis are explained in detail. . from Excel Regression Statistics Multiple R 0.172306 R Square 0.029689 Adjusted R Square 0.001151 Standard Error 0.352328 Observations 36 ANOVA df SS MS F Significance F Regression 1 0.129141 0.129141 1.040326 0.314948704 Residual 34 4.220582 0.124135 Total 35 4.349722 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 5.1302975 0.179009596 28.6593 2.1E-25 4.766506281 5.4940888 4.76650628 5.
49408881 X Variable 1 0.0376321 0.036895473 1.01996 0.31495 -0.03734857 0.1126127 -0.0373486 0.11261267 Graph Key components of the regression analysis Dependent Variable Slope Y-intercept Equation Intrinsic 0.169682348 4.427844793 Benefits= 4.427844793 + 0.16982348*(Intrinsic) 0.16493309 Extrinsic -0.16220711 6.157338158 Benefits= 6.157338158 -0.16220711*(Extrinsic) 0.287582114 Overall 0.0376321 5.1302975 Benefits= 5.1302975 + 0.0376321*(Overall) 0.0296894 Similarities and Differences Similarity: the intercepts of all the three regressions are positive and significant at 5% level of significance (as the p-value for all the 3 regressions are less than 0.05) Dissimilarity: The correlation between benefits-total job satisfaction and benefits-intrinsic job satisfaction is positive (as the slope between them is positive) but the correlation between benefits-extrinsic job satisfaction is negative (as the slope between them is negative) The regression results between benefits-intrinsic job satisfaction and benefits-extrinsic job satisfaction is significant at 5% level of confidence (as the p-value for these two is less than 0.05) but the result of benefit-total job satisfaction came to be insignificant at 5% level of confidence.
Correlation coefficients The strongest correlation coefficient is between benefits and intrinsic job satisfaction. It is strongest because the said benefits must have been intrinsic components like having a “Sense of meaningfulness”, “sense of choice”, “sense of competence” and the “sense of progress” (Thomas, 2009). The benefits are more of intangible nature than monetary. It implies that in order to increase extrinsic job satisfaction as well as the total job satisfaction, the manager should give monetary benefits like perks, incentives, etc.
The intrinsic job satisfaction is directly and significantly related to the benefits therefore the ongoing system of benefits should also be continued by the manager.
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