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Week 5 Correlation and Regression- Solutions Equal Pay Student

Question # 00011456
Subject: Mathematics
Due on: 05/21/2014
Posted On: 04/03/2014 02:56 PM

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1.Create a correlation table for the variables in our Employee Salary Data Set. (Use analysis ToolPak or the StatPlus:mac LE software function Correlation.) a.Interpret the results. What variables seem to be important in seeing if we pay males and females equally for equal work?

2.Below is a regression analysis for salary being predicted/explained by the other variables in our sample (Mid, age, ees, sr, raise, and deg 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.
3.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.
4.Based on all of your results to date, is gender a factor in the pay practices of this company? Why or why not? Which is the best variable to use in analyzing pay practices - salary or compa? Why?
5.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?

Tags equal student solutions regreion correlation week salary analysis variables compa regreion factor variable tests equality question results practices used single correlation simpler hypothesis statements4based appropriate date gender include answering questionsnote sure test examination multiple anova life

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Week 5 Correlation and Regression- Solutions Equal Pay Student

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Tutorial Preview …being xxxxxxxxxxxxxxxxxxx by xxx other variables xx our sample xxxxxxxxx ees, xxx xxxxxx and xxx variables ) xxxxxx since salary xxx compa xxx xxxxxxxxx ways xxxxxxxxxxxx an employee’s xxxxxxx we do xxx want xx xxxx both xxxx in the xxxx regression )Ho: xxx regression xxxxxxxx xx not xxxxxxxxxxx Ha: The xxxxxxxxxx equation is xxxxxxxxxxx Ho: xxx…
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