Regression 101 and Discrimination

Do the usual explanations of statistics, and especially regression analysis, make your eyes glaze over? If so, join the very large club. Help is here from the Manhattan Institute. George Borjas has this article in the City Journal giving a nontechnical description of the use of regression in claims of discrimination, its difficulties, and why different experts can find different results from the same raw data.

The article discusses claims that Harvard discriminated against Asian applicants, the subject of a recent Supreme Court decision. The same principles apply to discrimination claims in criminal cases, including McCleskey v. Kemp (1987) and states with misguided and misnamed Racial Justice Acts.

I recommended reading the whole article. Here are a couple of key paragraphs on why what “studies show” “ain’t necessarily so.”

A general lesson can also be drawn from these expert reports. Almost always, the evidence depends heavily on the assumptions that researchers make to analyze the available data. Different assumptions, as we will see, can lead the data to “say” radically different things. The assumptions often reflect a researcher’s perception of what is proper to do in a certain context. Inevitably, different researchers have different opinions of exactly how a particular question should be framed or addressed. And these opinions play a role in determining the answer to the specific question that the researcher is examining.

To complicate matters, in the case of researchers preparing litigation reports, it makes sense to suspect that the assumptions made to analyze (or manipulate) the data may be influenced by the testimony that the researcher is expected to give. When the two sides in a case disagree on what counts as the “truth,” that disagreement determines which experts a particular side will rely on. Whom they trust will depend on the assumptions the experts have used in related previous research or previous cases. And each side must then decide how to frame and rationalize those assumptions in a way that makes it easy to sell their particular “truth” to the judge and the jury.

I would add that the problem in the second paragraph is not limited to litigation. In academia today, faculty members who want to get research funded, have a paper published in a prestigious journal, or gain tenure know very well that their research results should support and absolutely must not refute the answer mandated by woke dogma.