BUSN U5IP Research Paper Example | Topics and Well Written Essays - 750 words

BUSN U5IP - Research Paper ExampleUnit 5 reverse Analyses Introduction This assignment conducts three phone linear reverting tests for three pairs of separatist and dependent variables. The data used to conduct the tests were obtained from a survey conducted by AIU. The regression tests were conducted using Excels built-in function. The following paragraphs present the results and analyses of tests. Results of Tests circuit card 1 Regression Output of Variables Benefits vs. Intrinsic Job Satisfaction Regression Statistics Multiple R 0.030092219 R Square 0.000905542 Adjusted R square -0.004408791 exemplification Error 0.876576061 Observations 190 Coefficient Y- intercept 4.524522995 Slope 0.151207676 Note Benefits = X Intrinsic descent satisfaction = Y Figure 1. Regression line Benefits vs. Intrinsic job satisfaction card 2 Regression Output of Variables Benefits vs. Extrinsic Job Satisfaction Regression Statistics Multiple R 0.026855348 R Square 0.00072121 Adjusted R squar e -0.004594103 Standard Error 1.024951959 Observations 190 Coefficient Y- intercept 5.750215066 Slope -0.157769935 Note Benefits = X Extrinsic job satisfaction = Y Figure 2. Regression line Benefits vs. Extrinsic job satisfaction Table 3 Regression Output of Variables Benefits vs. ... nsic job satisfaction 0.15 4.52 Y = 4.52 + 0.15 X 0.000905542 Extrinsic job satisfaction -0.16 5.75 Y = 5.75 0.16 X 0.00072121 Overall job satisfaction -0.07 4.96 Y = 4.96 0.07 X 0.0001144390 Note Benefits = X Analysis of Results and Conclusion The assignment conducted three separate linear regression analyses in order to establish a relationship between independent and dependent variables obtained through a survey. The relationship between the two variables, in this case, is evince through the linear regression equation, y = a + bx. In this equation a is called intercept of Y-axis and b is called run of the regression line (University of New England, n.d.). The slope indicates how changes in val ues of independent variable affect changes of dependent variable. The slope b may receive a positive or a blackball value. A positive slope defines that the dependent variable adjoins as the independent increases while the negative implies dependent variable decreases while the independent variable increases. Table 4 displays one positive and two negative slopes. Thus, Y = 4.52 + 0.15 X defines that both Benefits and Intrinsic job satisfaction move in the same direction, which suggests that the increase of benefits increases intrinsic job satisfaction. However, Y = 5.75 0.16 X defines that the variables Benefits and Extrinsic job satisfaction move in different directions. It means an increase of Benefits decreases extrinsic job satisfaction. Regression equations Y = 5.75 0.16 X, and Y = 4.96 0.07 X demonstrate negative relationships between independent and dependent variables while Y = 4.52 + 0.15 X displays positive relationship between independent and dependent variables. The Excel regression statistics evaluates linear correlation coefficient