BUS 308

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See comments at the right of the data set.            
IDSalaryCompaMidpointAgePerformance RatingServiceGenderRaiseDegreeGender1Grade     
8231.000233290915.80FA The ongoing question that the weekly assignments will focus on is:  Are males and females paid the same for equal work (under the Equal Pay Act)?  
10220.956233080714.70FA Note: to simplfy the analysis, we will assume that jobs within each grade comprise equal work.
11231.00023411001914.80FA     
14241.04323329012160FA The column labels in the  table mean: 
15241.043233280814.90FA ID – Employee sample number Salary – Salary in thousands     
23231.000233665613.31FA Age – Age in years Performance Rating  – Appraisal rating (Employee evaluation score)
26241.043232295216.21FA Service – Years of service (rounded)Gender:   0 = male, 1 = female  
31241.043232960413.90FA Midpoint – salary grade midpoint    Raise – percent of last raise
35241.043232390415.31FA Grade – job/pay gradeDegree (0= BS\BA 1 = MS)
36231.000232775314.31FA Gender1 (Male or Female)Compa - salary divided by midpoint
37220.956232295216.21FA     
42241.0432332100815.70FA     
3341.096313075513.60FB     
18361.1613131801115.61FB     
20341.0963144701614.81FB     
39351.129312790615.51FB     
7411.0254032100815.70FC     
13421.0504030100214.71FC     
22571.187484865613.80FD     
24501.041483075913.81FD     
45551.145483695815.20FD     
17691.2105727553130FE     
48651.1405734901115.31FE     
28751.119674495914.41FF     
43771.1496742952015.51FF     
19241.043233285104.61MA     
25241.0432341704040MA     
40251.086232490206.30MA     
2270.870315280703.90MB     
32280.903312595405.60MB     
34280.903312680204.91MB     
16471.175404490405.70MC     
27401.000403580703.91MC     
41431.075402580504.30MC     
5470.9794836901605.71MD     
30491.0204845901804.30MD     
1581.017573485805.70ME     
4661.15757421001605.51ME     
12601.0525752952204.50ME     
33641.122573590905.51ME     
38560.9825745951104.50ME     
44601.0525745901605.21ME     
46651.1405739752003.91ME     
47621.087573795505.51ME     
49601.0525741952106.60ME     
50661.1575738801204.60ME     
6761.1346736701204.51MF     
9771.149674910010041MF     
21761.1346743951306.31MF     
29721.074675295505.40MF     
Score:Week 1.Measurement and Description - chapters 1 and 2                                                   
                                                          
                                                          
<1 point>1Measurement issues.  Data, even numerically coded variables, can be one of 4 levels -                                                
  nominal, ordinal, interval, or ratio.  It is important to identify which level a variable is, as                                               
  this impact the kind of analysis we can do with the data.  For example, descriptive statistics                                                
  such as means can only be done on interval or ratio level data.                                                  
  Please list under each label, the variables in our data set that belong in each group.                                                
  NominalOrdinalIntervalRatio                                                    
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
 b.For each variable that you did not call ratio, why did you make that decision?                                                
                                                          
                                                          
                                                          
                                                          
                                                          
<1 point>2The first step in analyzing data sets is to find some summary descriptive statistics for key variables.                                              
  For salary, compa, age, performance rating, and service; find the mean, standard deviation, and range for 3 groups: overall sample, Females, and Males.                                         
  You can use either the Data Analysis Descriptive Statistics tool or the Fx =average and =stdev functions.                                                
   (the range must be found using the difference between the =max and =min functions with Fx) functions.                                              
  Note: Place data to the right, if you use Descriptive statistics, place that to the right as well.                                               
    SalaryCompaAgePerf. Rat.Service                                                 
  OverallMean                                                      
   Standard Deviation                                                      
   Range                                                      
  FemaleMean                                                      
   Standard Deviation                                                      
   Range                                                      
  MaleMean                                                      
   Standard Deviation                                                      
   Range                                                      
                                                          
<1 point>3What is the probability for a:    Probability                                                
  a.       Randomly selected person being a male in grade E?                                                  
  b.      Randomly selected male being in grade E?                                                     
   Note part b is the same as given a male, what is probabilty of being in grade E?                                               
  c.     Why are the results different?                                                    
                                                          
<1 point>4For each group (overall, females, and males) find:   OverallFemaleMale                                             
 a.The value that cuts off the top 1/3 salary in each group.     Hint: can use these Fx functions                                         
 b.The z score for each value:        Excel's standize function                                          
 c.The normal curve probability of exceeding this score:     1-normsdist function                                          
 d.What is the empirical probability of being at or exceeding this salary value?                                                
 e.The value that cuts off the top 1/3 compa in each group.                                                  
 f.The z score for each value:                                                     
 g.The normal curve probability of exceeding this score:                                                  
 h.What is the empirical probability of being at or exceeding this compa value?                                                
 i.How do you interpret the relationship between the data sets?  What do they mean about our equal pay for equal work question?                                            
                                                          
                                                          
                                                          
<2 points>5.      What conclusions can you make about the issue of male and female pay equality?  Are all of the results consistent?                                              
  What is the difference between the sal and compa measures of pay?                                                 
                                                          
                                                          
  Conclusions from looking at salary results:                                                   
                                                          
                                                          
  Conclusions from looking at compa results:                                                   
                                                          
                                                          
  Do both salary measures show the same results?                                                   
                                                          
                                                          
  Can we make any conclusions about equal pay for equal work yet?                                                 
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                                                          
                
                 
                 
                 
                 
                 
                 
                 
                 
                 
                 
                 
                 
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