Your assignment this week will cover the course material from Week 5 and Week 6. In this assignment, you will use the HR dataset you used for your Week 4 assignment to: (1) select and conduct appropriate statistical tests to compare various HR dataset variables, and (2) demonstrate your understanding of bivariate regression analysis.
Please respond to the following items below in a single Word document (written in Times New Roman 12-point font, double spaced) and submit the single document through the Canvas assignments page. The assignment submission must conform to the APA-style report format and your responses must be supported with in-text references to the course material (readings, lectures). Please refer to the assignment rubric for additional details about how your assignment will be graded.
The Director of Human Resources has come to you with the following questions:
Do those who have filed a complaint differ from those who have not filed a complaint in terms of their average monthly work hours? Is this difference meaningful assuming a statistical significance threshold of 0.05? Why or why not? Do those who have filed a complaint differ from those who have not filed a complaint in terms of their salary level? [Note: you should assume the salary level is ordinal, i.e., salary level 1 is less than salary level 2 and salary level 2 is less than salary level 3]. Is this difference meaningful assuming a statistical significance threshold of 0.05? Why or why not? Are those who have not been promoted in the past five years more likely to have left than those who have been promoted in the past five years (i.e., is there a statistical association between promotions and whether an employee has left the company)? What is the correlation between performance level and average monthly work hours? What is the correlation between performance level and salary (assume salary is ordinal)? What is the correlation between filing complaints (using the nominal variable “filed_complaint”) and average monthly work hours? Create a scatterplot of average monthly work hours (as a predictor on the x-axis) and performance level (as an outcome on the y-axis) to determine whether those variables appear to demonstrate a linear relationship. Provide a picture of your scatterplot and a brief interpretation of the results (e.g., no relationship, very weak relationship, weak relationship, moderate relationship, strong relationship). Conduct a bivariate linear regression between average monthly work hours (predictor) and performance level (outcome). Provide a summary of your results including the appropriate output tables as described in the Hatcher (2013) Chapter 7 readings and examples.