To do: Construct a build-your-own-relevant-statistics-class kit.

Alexis Lerner, who took a couple of our courses on applied regression and communicating data and statistics, designed a new course, “Jews: By the Numbers,” at the University of Toronto:

But what does it mean to work with data and statistics in a Jewish studies course? For Lerner, it means not only teaching her students to work with materials like survey results, codebooks, archives and data visualization, but also to understand the larger context of data. . . .

Lerner’s students are adamant that the quantification and measurement they performed on survivor testimonies did not depersonalize the stories they examined, a stereotype often used to criticize quantitative research methods.

“Once you learn the methods that go into statistical analysis, you understand how it’s not reductionist,” says Daria Mancino, a third-year student completing a double major in urban studies and the peace, conflict and justice program. “That’s really the overarching importance of this course for the social sciences or humanities: to show us why quantifying something isn’t necessarily reductionist.” . . .

Lerner hopes her students will leave her class with a critical eye for data and what goes into making it. Should survey questions be weighted, for example? How large of a sample size is large enough for results to be reliable? How do we know that survey respondents aren’t lying? How should we calculate margins of error?

Lerner’s students will leave the course with the tools to be critical analysts, meticulous researchers and – perhaps most importantly – thoughtful citizens in an information-heavy world.

This sounds great, and of course the same idea could be used to construct a statistics course based on any minority group. You could do it for other religious minorities or ethnic groups or states or countries or political movements or . . . just about anything.

So here’s what I want someone to do: Take this course, abstract it, and make it into a structure that could be expanded by others to fit their teaching needs. Wouldn’t it be great if there were hundreds of such classes, all over the world, wherever statistics is taught?

A build-your-own-relevant-statistics-class kit.

Let’s take Lerner’s course as a starting point, because we have it already, and from there abstract what is needed to create a structure that others can fill in.

Tomorrow’s post: Instead of replicating studies with problems, let’s replicate the good studies. (Consider replication as an honor, not an attack.)