Question;**Week 5 Tab**Create a correlation table for the variables in our Employee Salary Data Set. (Use analysis ToolPak or StatPlus:mac LE function Correlation).Reviewing the data levels from week 1, what variables can be used in a Pearson?s Correlation Table (which is what Excel produces)?Place the table here.Using r= approximately.28 as the significant r value (at p =.05) for a correlation between 50 values, what variables are significantly related to salary? To compa?Looking at the above correlations ? both significant or not ? are there any surprises ? by that I mean any relationships you expected to be meaningful and are not, and vice-versa?Does this information help us answer our equal pay for equal work question?Below is a regression analysis for salary being predicted/explained by the other variables in our sample (Midpoint, age, performance rating, service, raise, and degree variables). Note: since salary and compa are different ways of expressing an employee?s salary, we do not want to have both used in the same regression. Please interpret the findings.Perform a regression analysis using compa as the dependent variable and the same independent variables as used in question 2. Show the result, and interpret your findings by answering the same questions.Note: be sure to include the appropriate hypothesis statements.Based on all of your results to date, is gender a factor in the pay practices of this company? If so, which gender gets paid more? How do we know? Which is the best variable to use in analyzing pay practices - salary or compa? Why? What is the most interesting or surprising thing about the results we got doing the analyses during the last 5 weeks?Why did the single factor tests and analysis (such as t and single factor ANOVA tests on salary equality) not provide a complete answer to our salary equality question? What outcomes in your life or work might benefit from a multiple regression examination rather than a simpler one variable test?
Paper#53301 | Written in 18-Jul-2015Price : $27