week 5 bus308

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Score: Week 5  Correlation and Regression                                              
<1 point> 1.     Create a correlation table for the variables in our data set. (Use analysis ToolPak or StatPlus:mac LE function Correlation.)                              
    a.  Reviewing the data levels from week 1, what variables can be used in a Pearson’s Correlation table (which is what Excel produces)?                            
    b. Place table here (C8):                                              
    c. Using r = approximately .28 as the signicant r value (at p = 0.05) for a correlation between 50 values, what variables are                              
      significantly related to Salary?                                            
      To compa?                                              
    d. 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?                                    
    e. Does this help us answer our equal pay for equal work question?                                      
<1 point> 2   Below is a regression analysis for salary being predicted/explained by the other variables in our sample  (Midpoint,                                
       age, performance rating, service,  gender, 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.)                                  
      Plase interpret the findings.                                            
      Ho: The regression equation is not significant.                                          
      Ha: The regression equation is significant.                                          
      Ho: The regression coefficient for each variable is not significant   Note: technically we have one for each input variable.                            
      Ha: The regression coefficient for each variable is significant   Listing it this way to save space.                                
      SUMMARY OUTPUT                                            
      Regression Statistics                                              
      Multiple R 0.9915591                                              
      R Square 0.9831894                                              
      Adjusted R Square 0.9808437                                              
      Standard Error 2.6575926                                              
      Observations 50                                              
      ANOVA                                           &

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