I'll give you an example.

They loved to talk about women in engineering. They'd show us stats like only 20% of Engineers are women, and only 19% of Engineering grads are women, and use both of these stats to support the idea that women are being discriminated against by tech companies.

I wrote that they were clearly misinterpreting the data. If only 19% of the Engineering graduate hiring pool is women, but 20% of the Engineers are women, their data does not support the conclusion that women are the subject of discriminatory hiring practices in Tech. You can never have 50% women hires if only 19% of the candidates are women. In fact diversity reporting gives clear incentive to hire a woman over a similarly qualified man, which is why at the most desirable tech jobs like Google, the talent is more than 25% women, and they are over-represented.

The problem here is obviously happening much earlier than hiring, and much earlier than college, you have to address this before students choose majors.

I'm clearly correct but I got an F. Imagine getting an F for using data science to interpret the data in the department that does data science. They would rather have me be woke and literally subvert the principles of data science they are supposed to be teaching.