By completing this module, you will learn how to:
• Use computer software to access and evaluate quantitative data
• Identify independent, dependent, and control variables
• Identify whether variables are categorical or continuous
• Understand the logic of relating variables
• Formulate descriptive hypotheses
• Produce and interpret univariate, bivariate, and multivariate tables and figures
• Observe how adding control variables changes (or does not change) results
• Recognize the difference between frequencies and percentages
• Distinguish between percent across (row percentages) and percent down (column percentages)
• Summarize empirical results by addressing policy-relevant questions
• Use demographic data to address policy-relevant questions
This module is designed for use in undergraduate sociology, demography, public policy, public health, or related social science courses that introduce students to quantitative reasoning and population data. It is well suited for lower- or upper-division courses, including introductory statistics, research methods, social inequality, health disparities, or labor and employment courses. The activity works well in small to medium-sized classes and can be completed individually or in pairs.
The module is structured as a guided, computer-based lab exercise using WebCHIP and typically requires 60–90 minutes to complete, depending on students’ familiarity with the software and with reading tables and figures. No special equipment is required beyond access to a computer with internet connectivity. Students do not need advanced statistical training, but they should have prior exposure to basic concepts such as percentages, categorical variables, and simple contingency tables. The module can be used as a standalone lab, an in-class activity with discussion, or a take-home assignment. It is easy to adapt for different instructional settings by shortening or expanding sections, emphasizing either methodological skills or substantive interpretation, or integrating it into a larger unit on inequality, health, or work.
This module explores how disability is measured and reported in U.S. Census data, with particular attention to the relationship between physical disability and employment disability. Students use descriptive quantitative methods to examine whether this relationship differs by race/ethnicity and to reflect on how social inequality and stigma shape the reporting and consequences of disability in the labor market.