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

BUSN U5IP - Research Paper Example Unit –5 Regression Analyses Introduction This assignment conducts three linear regression tests for three pairs of independent and dependent variables. The data used to conduct the tests were obtained from a survey conducted by AIU. The regression tests were conducted using Excel’s built-in function. The following paragraphs present the results and analyses of tests. Results of Tests Table 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 Standard Error 0.876576061 Observations 190    Coefficient Y- intercept 4.524522995 Slope 0.151207676 Note: Benefits = X; Intrinsic job satisfaction = Y Figure 1. Regression line Benefits vs. Intrinsic job satisfaction Table 2 Regression Output of Variables Benefits vs. Extrinsic Job Satisfaction Regression Statistics Multiple R 0.026855348 R – Square 0.00072121 Adjusted R square -0.004594103 Standar d 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 expressed through the linear regression equation, y = a + bx. In this equation a is called intercept of Y-axis and b is called slope of the regression line (â€Å"University of New England†, n.d.). The slope indicates how changes in values of independent variable affect changes of dependent variable. The slope b may receive a positive or a negative value. A positive slope defines that the dependent variable increases as the independent increases while the negative implies dependent vari able 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