BUS308: Statistics for Managers

profilea23ars

Problem Set Week Two

In the Week Two Assignment sheet, complete problems 1-5 below and submit your work in an Excel document. Be sure to show all of your work and clearly label all calculations. All statistical calculations will use the Employee Salary Data Set and Weekly Assignment Sheet (Both Attached)

(Note: Questions 1- 4 have additional elements to respond to below the analysis results and included in the Week Two Assignment sheet are 2 one-sample t-tests comparing male and female average salaries to the overall sample mean.)

 

Week 2Testing means - T-tests            
 In questions 2, 3, and 4 be sure to include the null and alternate hypotheses you will be testing.         
 In the first 4 questions use alpha = 0.05 in making your decisions on rejecting or not rejecting the null hypothesis.      
               
1Below are 2 one-sample t-tests comparing male and female average salaries to the overall sample mean.        
 (Note: a one-sample t-test in Excel can be performed by selecting the 2-sample unequal variance t-test and making the second variable = Ho value - a constant.) 
 Note:  These values are not the same as the data the assignment uses.  The purpose is to analyze the results of t-tests rather than directly answer our equal pay question.
 Based on these results, how do you interpret the results and what do these results suggest about the population means for male and female average salaries? 
               
 Males   Females         
 Ho: Mean salary =45.00  Ho: Mean salary =45.00        
 Ha: Mean salary =/=45.00  Ha: Mean salary =/=45.00        
               
 Note: While the results both below are actually from Excel's t-Test: Two-Sample Assuming Unequal Variances,       
 having no variance in the Ho variable makes the calculations default to the one-sample t-test outcome - we are tricking Excel into doing a one sample test for us. 
  MaleHo  FemaleHo       
 Mean5245 Mean3845       
 Variance3160 Variance334.6670       
 Observations2525 Observations2525       
 Hypothesized Mean Difference0  Hypothesized Mean Difference0        
 df24  df24        
 t Stat1.968903827  t Stat-1.91321        
 P(T<=t) one-tail0.03030785  P(T<=t) one-tail0.03386        
 t Critical one-tail1.71088208  t Critical one-tail1.71088        
 P(T<=t) two-tail0.060615701  P(T<=t) two-tail0.06772        
 t Critical two-tail2.063898562  t Critical two-tail2.0639        
 Conclusion: Do not reject Ho; mean equals 45Conclusion: Do not reject Ho; mean equals 45      
Note: the Female results are done for you, please complete the male results.         
 Is this a 1 or 2 tail test?   Is this a 1 or 2 tail test?2 tail        
 - why?   - why?Ho contains =       
 P-value is:   P-value is:0.06772        
Is P-value < 0.05 (one tail test) or 0.025 (two tail test)?  Is P-value < 0.05 (one tail test) or 0.025 (two tail test)?No        
Why do we not reject the null hypothesis?  Why do we not reject the null hypothesis?P-value greater than (>) rejection alpha     
               
 Interpretation of test outcomes:             
               
2Based on our sample data set, perform a 2-sample t-test to see if the population male and female average salaries could be equal to each other.   
 (Since we have not yet covered testing for variance equality, assume the data sets have statistically equal variances.)     
               
 Ho: Male salary mean = Female salary mean         
 Ha: Male salary mean =/= Female salary mean         
 Test to use:t-Test: Two-Sample Assuming Equal Variances         
               
               
               
               
               
               
               
               
               
               
               
               
               
              
              
               
 P-value is:             
 Is P-value < 0.05 (one tail test) or 0.025 (two tail test)?             
 Reject or do not reject Ho:             
If  the null hypothesis was rejected, calculate the effect size value:             
If calculated, what is the meaning of effect size measure:             
               
 Interpretation:             
               
b.Is the one or two sample t-test the proper/correct apporach to comparing salary equality?  Why?       
               
               
3Based on our sample data set, can the male and female compas in the population be equal to each other? (Another 2-sample t-test.)    
 Again, please assume equal variances for these groups.          
 Ho:             
 Ha:             
 Statistical test to use:             
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
 What is the p-value:             
 Is P-value < 0.05 (one tail test) or 0.025 (two tail test)?             
 Reject or do not reject Ho:             
If  the null hypothesis was rejected, calculate the effect size value:             
If calculated, what is the meaning of effect size measure:             
               
  Interpretation:              
               
4Since performance is often a factor in pay levels, is the average Performance Rating the same for both genders?      
 NOTE: do NOT assume variances are equal in this situation.         
 Ho:             
 Ha:             
               
 Test to use:t-Test: Two-Sample Assuming Unequal Variances         
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
  What is the p-value:            
 Is P-value < 0.05 (one tail test) or 0.025 (two tail test)?            
  Do we REJ or Not reject the null?            
               
 If  the null hypothesis was rejected, calculate the effect size value:            
 If calculated, what is the meaning of effect size measure:            
               
  Interpretation:            
               
               
5If the salary and compa mean tests in questions 2 and 3 provide different results about male and female salary equality,        
 which would be more appropriate to use in answering the question about salary equity?  Why?       
               
               
 What are your conclusions about equal pay at this point?          
  • 10 years ago
  • 12
Answer(3)

Purchase the answer to view it

blurred-text
NOT RATED
  • attachment
    test_for_mean.xlsx

Purchase the answer to view it

blurred-text
NOT RATED
  • attachment
    bus308_week_2_solution.xlsx

Purchase the answer to view it

blurred-text
NOT RATED
  • attachment
    bus308_student_assignment_file_4.13.16_week_2.xlsx