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.
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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.
Mean
Standard Deviation
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?
