Teaching your students about bias in statistics

One thing I like to emphasize to my students is that just because a scientist is using math and science and statistics, it doesn't mean they are unbiased. I usually describe how Sir RA Fisher love statistics, smoking, and white folks and, shock of shocks, produced data that supported both the safety of smoking and the soundness of eugenics. 

For more on that: How Eugenics Shaped Statistics, by Clayton for Nautilus Magazine.

And now I have another plug-and-play, easy-to-implement example of checking your bias in your research.

http://journals.sagepub.com/doi/abs/10.1177/0098628320979879

The article makes a sound argument: While social justice/bias issues may be present in other psychology courses, they need to be addressed in our stats classses as well. 

This journal article from Teaching of Psychology suggests that a lecture that highlights Samuel George Morton's "research" that investigated skull size and intelligence, as well as more modern examples of bias, leads to an increase of student scores on various social justice scales. To sum up the spirit of the article, see the highlighted bit below:  

The group also highlighted more contemporary work. Here is a quick summary of what they shared in the experimental lecture, a lecture that they share as supplemental material:

While I (and the authors of this piece) acknowledge that one lecture typically isn't enough to get any point across, including the lesson of bias is research...this is a good, engaging start to that journey for our psychology majors and statistics students.