There
are many studies that show women earn less than men. This, however, remains a
very hot topic across industries with many people criticizing each study for
ignoring factors that could be the reason behind gender pay gap (e.g. women
working part time, women being less represented in high-paying jobs in the tech
industry, etc.).
A
large research university wants to make sure that their graduate students who
have “assistant” positions are treated fairly without a gender bias. The
stipend (known as “assistantship”) the teaching and research assistants receive
consists of a tuition waiver plus some cash amount, available to the graduate
student for up to six years.
A
study has been initiated and data on 1,000 graduate student assistants have
been compiled. For each student, the following information was recorded:
·
Assistantship
(Stipend): Annual stipend in dollars;
·
Gender: F, female; or
M, male;
·
Field of Study: S,
science, including the natural sciences and engineering; A, arts, including
both liberal and fine arts, and humanities;
·
Year of Study: year
of the student’s graduate studies at the beginning of their contract
period;
·
Marital Status: M,
married; or S, single
At
first, an analysis was done to see if the there was a gender gap in pay. The
following table is the result of this analysis:
Some
have also expressed a concern that the first analysis is too simplistic since a
pay gap could be due to the field of study. So, an analysis on the field of
study was also conducted which has resulted in the following:
However, there is
still much uncertainty about any conclusion one can make about the issue of
gender gap in student compensation based on the results of studies that only
focus on one of the characteristics of the student body at a time and do not
consider the impact of other variables.
You have been asked
to help in bringing more clarity to this question.
·
Use data in the Excel
file to analyze the impact of the explanatory variables on the Assistantship
(Stipend).
·
As you move forward
with your analysis, you should include the Excel output obtained at each step
and refer to it in your narrative explanation.
·
If you eliminate any
of the variables from consideration, you should clearly explain why you have
done so.
·
In short, you should
back all your findings with the analysis that has been conducted to reach each
conclusion.
Does your analysis
contradict or confirm the original belief about role of gender and pay? Why?
What is the advantage (if any) of using regression analysis compared to the
two-sample t-tests (shown above)?
Should the University
be concerned about gender pay gap in compensation of its graduate assistants?
What avenues do you recommend it should explore to further study and/or address
this issue?
Insert your response
to the questions posed in the below, including output from your Excel-based
analysis, here:
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