Async-03: Addressing Diversity, Inclusion, and Equality in a Methods Course

Date/Time: N/A

By Steven Foti (University of Florida)


In an effort to more openly address diversity, equity, and inclusion, many statistics educators are being encouraged to inject new content into their courses related to these topics. While statistics education has emphasized the importance of using real data scenarios in the classroom, channeling student discussions toward diversity, equity, and inclusion is not a trivial task. In this session, I will share an assignment that I used in a masters-level biostatistical methods course to push my students to engage with these topics through a dataset on insurance redlining. In addition to presenting a specific example, I will share a more general blueprint for this activity in hopes that participants draw inspiration to create similar assignments with different data contexts.

Excerpt from module instructions:
Finally, while this textbook chapter existed long before 2020, I think the context of this chapter presents a nice opportunity to discuss the roles that statistics and data analysis play in discussions about diversity and equality. As you will see in the chapter, the author makes some commentary about politics vs. statistics, and I encourage you to think more deeply about these concepts. Statistics and data are powerful tools for debate in our modern world, and we must be sure that we are appropriately and justifiably using statistics to give our best interpretations of what relevant data is telling us.
Additional resources provided:
Chicago Tribune - Insurer Redlining Banned (1992, article) Link:,redlining''%20by%20insurance%20companies
The textbook chapter makes a brief mention about the gender pay gap in the United States. Here is a 2018 article about the (relatively) current state of the issue from 538 (the blog run by Nate Silver, a statistician that is typically involved in politics and sports). Link:
Discussion instructions:
After working through Module 10, please write a short post about your thoughts on the role statistics/statisticians play in discussions regarding diversity, inclusion, and equality. I understand this is a vague topic, but some potential areas to consider: research questions, data collection, stratification, sampling, model selection, study design, etc.
In addition to your post, please read through the posts of your classmates and try to respond to at least one.
For full points on this assignment, I am looking for 1 post and 1 response from each of you.