Investigating the Effects of Race and Gender on Earnings in the United States


Jill Bouma
Berea College

Students will look at inequality in America. Often, we think of power and inequality - in terms of money. Who has more money, and thus, in general, more access to opportunities and resources? Who makes the most money, and who makes the least? Does income differ for men and women, and for whites and people of color? In this exercise, we will examine earnings data for all full-time workers in the US. Students will be able to examine data for the nation as a whole, for Kentucky, and for a state of their choosing.

Learning Goals

Using software to access and analyze census data
Identifying independent and dependent variables
Forming testable hypotheses using quantitative data
Quantitative writing
Learning how to construct, read, and interpret bivariate tables displaying frequencies and percentages

Examine the influence of race and gender on earnings using 2008 American Community Survey data from the U.S. Census Bureau. Do women really make less than men? Do people of color actually make less than whites?
Compare national, regional and state data. How does Kentucky rank in terms of income inequality compared to national data? How do other states compare to KY and to the nation as a whole?

Context for Use

This activity is used in a Problems in American Institutions class for undergraduate students. This activity explores topics of race/ethnicity and gender on earnings in the United States.

Description and Teaching Materials

Teaching Notes and Tips

This activity uses customized data sets made from the 2008 American Community Survey at the national and state level. It guides students through data manipulation using WebCHIP software found at DataCounts!. To open WebCHIP with the dataset for the activity, please see instructions and links in the exercise documents under teaching materials. For more information on how to use WebCHIP, see the How To section on DataCounts!


References and Resources

This exercise is based on a module developed by Tim Thornton, SUNY-Brockport.

File Attachment(s)