Multiple Linear Regression - Job Satisfaction
Multiple linear regression is a logical extension to the Pearson Product-Moment Correlation test. Researchers use multiple linear regression to examine the relationship between at least two predictor variables and a scale (numerical) dependent variable. Multiple linear regression is the most commonly used statistical test for quantitative DBA studies.
Run a multiple linear regression using the Week 6 Data File for Multiple Linear Regression. You will use "job satisfaction" as the dependent variable.
Submit a synthesis of statistical findings derived from multiple regression analysis:
• An APA Results section for the multiple regression test [see an example in Lesson 34 of the Green and Salkind (2017) text].
• Only the critical elements of your SPSS output:
o Research question
o H10 (null) and H1a (alternate) hypothesis
o Descriptive statistics narrative and properly formatted descriptive statistics table
o Scatterplot graph
o Inferential APA Results Section to include a Normal Probability Plot (P-P) of the Regression Standardized Residual and the scatterplot of the standardized residuals
o An Appendix including the SPSS output generated for descriptive and inferential statistics
• An explanation of the differences and similarities of bivariate regression analysis and multiple regression analyses.© SolutionLibrary Inc. solutionlibary.com 9836dcf9d7 https://solutionlibrary.com/statistics/descriptive-statistics/multiple-linear-regression-job-satisfaction-j819