Week 5 BUS 308 Assignment

 

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.          
                    
1Create 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?          
                    
2Below 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 R0.99215498                 
 R Square0.9843715                 
 Adjusted R Square0.98176675                 
 Standard Error2.59277631                 
 Observations50                 
                    
 ANOVA                  
  dfSSMSFSignificance F             
 Regression717783.72540.52377.9148.44043E-36             
 Residual42282.3456.72249               
 Total4918066                
                    
  CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0%          
 Intercept-4.0093.775-1.0620.294-11.6273.609-11.6273.609          
 Mid1.2200.03040.6740.0001.1591.2801.1591.280          
 Age0.0290.0670.4390.663-0.1050.164-0.1050.164          
 EES-0.0960.047-2.0200.050-0.1910.000-0.1910.000          
 SR-0.0740.084-0.8760.386-0.2440.096-0.2440.096          
 G2.5520.8473.0120.0040.8424.2610.8424.261          
 Raise0.8340.6431.2990.201-0.4622.131-0.4622.131          
 Deg1.0020.7441.3470.185-0.5002.504-0.5002.504          
                    
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?            
                    
                    
3Perform 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.             
                    
4Based 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?            
                    
                    
5Why 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?         
        
  • 11 years ago
A+++++++++++ Solution
NOT RATED

Purchase the answer to view it

blurred-text
  • attachment
    week_5-bus.xlsx