# Week 4 tab, Use data on 1st tab.

## Answer To: Week 4 tab, Use data on 1st tab.

Pooja answered on Mar 21 2021
Data
ID    Salary    Compa-ratio    Midpoint     Age    Performance Rating    Service    Gender    Raise    Degree    Gender1    Grade        Do not manipuilate Data set on this page, copy to another page to make changes
1    57.7    1.012    57    34    85    8    0    5.7    0    M    E        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)?
2    27.9    0.899    31    52    80    7    0    3.9    0    M    B        Note: to simplfy the analysis, we will assume that jobs within each grade comprise equal work.
3    36.2    1.168    31    30    75    5    1    3.6    1    F    B
4    63.7    1.117    57    42    100    16    0    5.5    1    M    E        The column labels in the table mean:
5    45.5    0.
947    48    36    90    16    0    5.7    1    M    D        ID – Employee sample number             Salary – Salary in thousands
6    74.4    1.110    67    36    70    12    0    4.5    1    M    F        Age – Age in years            Performance Rating - Appraisal rating (employee evaluation score)
7    42.1    1.052    40    32    100    8    1    5.7    1    F    C        Service – Years of service (rounded)            Gender – 0 = male, 1 = female
8    22.8    0.992    23    32    90    9    1    5.8    1    F    A        Midpoint – salary grade midpoint             Raise – percent of last raise
9    77.7    1.159    67    49    100    10    0    4    1    M    F        Grade – job/pay grade            Degree (0= BS\BA 1 = MS)
10    23    0.998    23    30    80    7    1    4.7    1    F    A        Gender1 (Male or Female)            Compa-ratio - salary divided by midpoint
11    21.8    0.949    23    41    100    19    1    4.8    1    F    A
12    55.5    0.973    57    52    95    22    0    4.5    0    M    E
13    40.5    1.012    40    30    100    2    1    4.7    0    F    C
14    23.6    1.028    23    32    90    12    1    6    1    F    A
15    23.4    1.016    23    32    80    8    1    4.9    1    F    A
16    42.3    1.058    40    44    90    4    0    5.7    0    M    C
17    67.5    1.184    57    27    55    3    1    3    1    F    E
18    34.1    1.101    31    31    80    11    1    5.6    0    F    B
19    24.3    1.056    23    32    85    1    0    4.6    1    M    A
20    35.2    1.135    31    44    70    16    1    4.8    0    F    B
21    79.1    1.181    67    43    95    13    0    6.3    1    M    F
22    51.1    1.065    48    48    65    6    1    3.8    1    F    D
23    25.3    1.101    23    36    65    6    1    3.3    0    F    A
24    51    1.063    48    30    75    9    1    3.8    0    F    D
25    23    1.000    23    41    70    4    0    4    0    M    A
26    24.4    1.060    23    22    95    2    1    6.2    0    F    A
27    42.9    1.073    40    35    80    7    0    3.9    1    M    C
28    77.2    1.152    67    44    95    9    1    4.4    0    F    F
29    77.5    1.157    67    52    95    5    0    5.4    0    M    F
30    46.2    0.963    48    45    90    18    0    4.3    0    M    D
31    22.7    0.985    23    29    60    4    1    3.9    1    F    A
32    27.2    0.876    31    25    95    4    0    5.6    0    M    B
33    62.9    1.104    57    35    90    9    0    5.5    1    M    E
34    28.1    0.905    31    26    80    2    0    4.9    1    M    B
35    23.9    1.038    23    23    90    4    1    5.3    0    F    A
36    22.8    0.993    23    27    75    3    1    4.3    0    F    A
37    22.6    0.984    23    22    95    2    1    6.2    0    F    A
38    60    1.052    57    45    95    11    0    4.5    0    M    E
39    33.5    1.081    31    27    90    6    1    5.5    0    F    B
40    23    1.002    23    24    90    2    0    6.3    0    M    A
41    42.1    1.052    40    25    80    5    0    4.3    0    M    C
42    24.1    1.049    23    32    100    8    1    5.7    1    F    A
43    74.5    1.112    67    42    95    20    1    5.5    0    F    F
44    63.8    1.120    57    45    90    16    0    5.2    1    M    E
45    48.9    1.018    48    36    95    8    1    5.2    1    F    D
46    61.8    1.085    57    39    75    20    0    3.9    1    M    E
47    61.5    1.079    57    37    95    5    0    5.5    1    M    E
48    65.6    1.150    57    34    90    11    1    5.3    1    F    E
49    54.9    0.963    57    41    95    21    0    6.6    0    M    E
50    61.9    1.086    57    38    80    12    0    4.6    0    M    E
Week 1
Week 1: Descriptive Statistics, including Probability
While the lectures will examine our equal pay question from the compa-ratio viewpoint, our weekly assignments will focus on
examining the issue using the salary measure.
The purpose of this assignmnent is two fold:
1. Demonstrate mastery with Excel tools.
2. Develop descriptive statistics to help examine the question.
3. Interpret descriptive outcomes
The first issue in examining salary data to determine if we - as a company - are paying males and females equally for doing equal work is to develop some
descriptive statistics to give us something to make a preliminary decision on whether we have an issue or not.
1    Descriptive Statistics: Develop basic descriptive statistics for Salary
The first step in analyzing data sets is to find some summary descriptive statistics for key variables.
Suggestion: Copy the gender1 and salary columns from the Data tab to columns T and U at the right.
Then use Data Sort (by gender1) to get all the male and female salary values grouped together.
a.     Use the Descriptive Statistics function in the Data Analysis tab                                 Place Excel outcome in Cell K19
to develop the descriptive statistics summary for the overall
group's overall salary. (Place K19 in output range.)
Highlight the mean, sample standard deviation, and range.
b.    Using Fx (or formula) functions find the following (be sure to show the formula
and not just the value in each cell) asked for salary statistics for each gender:
Male    Female
Mean:
Sample Standard Deviation:
Range:
2    Develop a 5-number summary for the overall, male, and female SALARY variable.
For full credit, show the excel formulas in each cell rather than simply the numerical answer.
Overall    Males    Females
Max
3rd Q
Midpoint
1st Q
Min
3    Location Measures: comparing Male and Female midpoints to the overall Salary data range.
For full credit, show the excel formulas in each cell rather than simply the numerical answer.
Using the entire Salary range and the M and F midpoints found in Q2                            Male    Female
a. What would each midpoint's percentile rank be in the overall range?                                    Use Excel's =PERCENTRANK.EXC function
b. What is the normal curve z value for each midpoint within overall range?                                    Use Excel's =STANDARDIZE function
4    Probability Measures: comparing Male and Female midpoints to the overall Salary data range
For full credit, show the excel formulas in each cell rather than simply the numerical answer.
Using the entire Salary range and the M and F midpoints found in Q2, find                            Male    Female
a. The Empirical Probability of equaling or exceeding (=>) that value for                                    Show the calculation formula = value/50 or =countif(range,">="&cell)/50
b. The Normal curve Prob of => that value for each group                                    Use "=1-NORM.S.DIST" function
5    Conclusions: What do you make of these results?                    Be sure to include findings from this week's lectures as well.
In comparing the overall, male, and female outcomes, what relationship(s) see, to exist between the data sets?
What does this suggest about our equal pay for equal work question?
Week 2
Week 2: Identifying Significant Differences - part 1
To Ensure full credit for each question, you need to show how you got your results. This involves either showing where the data you used is located
or showing the excel formula...
SOLUTION.PDF