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Measuring Wellbeing across Racial Groups using Data and Statistics

Jenny Wahl, Carleton College economics department, authored this page.
Author Profile
This material was originally developed as part of the Carleton College Teaching Activity Collection
through its collaboration with the SERC Pedagogic Service.


This set of assignments exposes students to statistics and data pertaining to economic well-being over time across racial categories. Assignment 1 asks students to examining data on height and other characteristics (including skin color) of antebellum convicts and to evaluate whether these data are useful in assessing economic well-being. Assignment 2 requests students to retrieve several tables of statistical information concerning income, education, life expectancy, and other potential measures of well-being from the U.S. Census Bureau and other sources, and to analyze various simple statistics over time and across racial categories. Assignment 3 requires students to work with ipums census data from 1940, 1970, and 2000 to answer a series of questions exploring racial differences in labor-market outcomes over time. Assignment 4 asks students to compile information obtained in earlier assignments (as well as in class readings) and write a paper exploring racial differences in well-being in the U.S. at various points in time and over time.

Learning Goals

  • Acquire knowledge of racial gaps in the U.S. over time
  • Enhance ability to obtain data and statistics from numerous sources and to identify what is useful (and what is not) as they explore particular questions
  • Think critically about what we mean by "well-being" and how we might measure and represent it
  • Learn how to use charts and graphs as powerful supporting illustrations
  • Write clearly and effectively using data and statistics

Context for Use

I crafted these assignments for a class of 25 students, all of whom have had principles of economics. They will also have had lectures covering basic statistics – means, medians, probability density functions, correlation, simple regression analysis – as well as a review of Excel and SPSS tools. Although the assignments could fit different upper-level classes (for instance, labor economics, economics of race, and economics of inequality), I plan to use them in a cliometrics course that assigns readings on slavery, school segregation, and other racial issues. My course will also include a lecture and readings on the use of height as a surrogate for economic well-being.

Description and Teaching Materials

The online course folder contains four assignments, each designed to advance student knowledge about and understanding of racial (black-white) differences in the U.S. over time. Three result in written papers, supported by attached tables and charts; one asks students to answer a series of questions using census data from three different years.


Teaching Notes and Tips

I intend for these assignments to help students get a feel for the messiness of data work so that they will be better-equipped to do their own empirical analysis and to appreciate (and criticize) the efforts of other empirical researchers. The assignments will also bring out the difference between data and statistics, and drive home the importance of the unit of observation. Although some students may resist delving into code books, I craft questions about missing values, variable definitions, and topcoding so they can't avoid doing so. Hopefully, the results will interest them enough that they begin to understand how careful researchers must be with data.

I provide some data and statistical tables directly but ask students to download other tables themselves. The former allows me to isolate variables and focus student attention on analysis; the latter gives students some expertise at finding and manipulating publicly available information.

I expect that students will need guidance in presenting information in tables and graphs. I will offer good and bad examples of charts in lectures and in readings so that they acquire templates.

I ask students to write short papers (3, 5, and 7 pages long) but allow them to add whatever supporting graphs and tables they want as long as they justify inclusion. I hope that this approach will teach them to distill large amounts of quantitative information into concise readable text and to think carefully about how charts can enhance (and not detract from) their presentations. Picking and choosing what to include as supporting evidence is a key feature of each paper, and I will stress how important this is for effective and persuasive writing.


Most of the assignments are papers; one is a series of answers to specific questions. I assess students on the quality of their writing and of their interweaving of prose and quantitative information (both within the text and in attached charts). I also gauge how well they present data and statistics, particularly whether they include too much or too little in supporting documents. I provide them with tips for good writing (gleaned from Strunk and White, Zinsser, Garner, and the Chicago Manual of Style).

References and Resources

Please see urls contained within the assignments.