The "Berekley gender bias case" section made it make sense to me. Every single department was more likely to admit a woman than a man, and yet the school as a whole was more likely to admit a man than a woman.
This was because women were applying to more competitive departments, on average, so a lower percentage of women applicants were getting admitted.
> Every single department was more likely to admit a woman than a man
Not quite; you can see several exceptions to this in the table in the article.
The key points of the partitioned data were:
No department was significantly biased against women.
Most departments had a statistically significant bias towards women.
It's interesting to note that the departments that ARE biased towards men have more female applicants; I wonder if being in a minority group for that department is an even more important confounding factor.
Another example which recently made the news is comparing education systems of Wisconsin and Texas. Each ethnic group in Texas performs better than in Wisconsin, but Wisconsin has fewer of the low performing groups and therefore has higher test score averages.
In my high school stats class the example that was used was 2 airlines, one of which had better on-time arrival rates at every airport, yet in sum had a worse on-time arrival rate due to where more flights emanated from.
The examples definitely help. The Civil Rights vote did it for me:
* The South voted against it overwhelmingly.
* Democrats voted for it (compared to Republicans)
* But, because the Democrats had the majority of the Southern seats their overall vote was against it. So, whichever party had the Southern seats was going to come out as voting against, compared to the other party
This was because women were applying to more competitive departments, on average, so a lower percentage of women applicants were getting admitted.