It's especially sad that our societal views are so far off the data due to stereotyping.
According to some CDC studies, more men are victims of domestic abuse than women are. It's just that men do not report much of it, and there are more cases of severe injuries when it comes to women (40/60 split). I think one of those CDC studies even said that men are more likely to have a deadly weapon used against them in a domestic abuse situation than women are. A little shocking how different this is from the typical narrative.
The problem is how we deal with outliers. Statisticians know that outliers need to be excluded from their results, but society tends to focus on outliers, letting everyone else lay in their shadow.
We're all guilty of it. We have competitions with the sole purpose of finding these extreme outliers. We look up to them, turn them into household names, reward them with great wealth and accolades.
It turns out if you look for outliers, you will find mostly men. Pick any attribute you can measure and you'll probably find a man who "wins". Fastest human? Male. Greatest chess player? Male. Worst serial killer? Male.
This is vaguely recognised which is why women are held to different standards. They have their own sporting events, for example, otherwise they would all fall into the shadow of the all-male outliers.
Nobody minds that 99% of men fall into that same shadow, though.
In car insurance it's quite well-known that men, on average, are responsible for higher payouts. But this isn't because men, on average, do more damage to cars. In fact, the statistics show the opposite. But when women damage cars it tends to be below the threshold that is worth claiming. When a car is completely written off, it tends to be due to a man. It's a tiny minority of incidents, but has a huge impact on insurance payouts.
As with anything, people focus on the extremes and the extremes are mostly male. But that doesn't mean every male is responsible or even capable of the same. But, as with insurance, we all suffer from it.
> Statisticians know that outliers need to be excluded from their results,
offtopic, but this is not true in general. This is one of my strongest pet peeves. For many distributions (e.g. Cauchy, power laws, Levy stable...) it turns out that all samples are "outliers" and you cannot really exclude them. It is only on the "degenerate" case of finite variance that you can exclude outliers. But some statisticians may still argue that this is still wrong: there are no outliers, only incomplete models.
According to some CDC studies, more men are victims of domestic abuse than women are. It's just that men do not report much of it, and there are more cases of severe injuries when it comes to women (40/60 split). I think one of those CDC studies even said that men are more likely to have a deadly weapon used against them in a domestic abuse situation than women are. A little shocking how different this is from the typical narrative.