Week 5 bus 308 | Business & Finance homework help

Week 5 Correlation and Regression                                   For each question involving a statistical test below, list the null and alternate hypothesis statements.  Use .05 for your significance level in making your decisions.                 For full credit, you need to also show the statistical outcomes – either the Excel test result or the calculations you performed.                                                             1 Create a correlation table for the variables in our data set. (Use analysis ToolPak 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.)                                                                   Ho: The regression equation is not significant.                                 Ha: The regression equation is significant.                                 Ho: The regression coefficient for each variable is not significant                             Ha: The regression coefficient for each variable is significant                                                                     Sal     The analysis used Sal as the y (dependent variable) and                           SUMMARY OUTPUT   mid, age, ees, sr, g, raise, and deg as the dependent                                  variables (entered as a range).                             Regression Statistics                                     Multiple R 0.99215498                                     R Square 0.9843715                                     Adjusted R Square 0.98176675                                     Standard Error 2.59277631                                     Observations 50                                                                             ANOVA                                         df SS MS F Significance F                             Regression 7 17783.7 2540.52 377.914 8.44043E-36                             Residual 42 282.345 6.72249                                 Total 49 18066                                                                             Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%                       Intercept -4.009 3.775 -1.062 0.294 -11.627 3.609 -11.627 3.609                       Mid 1.220 0.030 40.674 0.000 1.159 1.280 1.159 1.280                       Age 0.029 0.067 0.439 0.663 -0.105 0.164 -0.105 0.164                       EES -0.096 0.047 -2.020 0.050 -0.191 0.000 -0.191 0.000                       SR -0.074 0.084 -0.876 0.386 -0.244 0.096 -0.244 0.096                       G 2.552 0.847 3.012 0.004 0.842 4.261 0.842 4.261                       Raise 0.834 0.643 1.299 0.201 -0.462 2.131 -0.462 2.131                       Deg 1.002 0.744 1.347 0.185 -0.500 2.504 -0.500 2.504                                                             Interpretation:  Do you reject or not reject the regression null hypothesis?                             Do you reject or not reject the null hypothesis for each variable?                             What is the regression equation, using only significant variables if any exist?                           What does result tell us about equal pay for equal work for males and females?                                                                                                         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?