What is the fallacy / bias where the sample is taken after the fact?

Question

I came across a post on Facebook which tried to celebrate how the "old ways" (when we were kids) are better, which went along the lines of:

Like this post if you used to cycle around on your bike as a kid without a helmet and survived.

(attempting to prove that kids these days are too "wrapped in cotton wool" and that the "need" for kids to wear helmet while cycling was just paranoia)

The obvious flaw is that anyone who cycled their bike without a helmet and didn't survive are not in a position to argue / do an angry face, so there will be an inherent bias in the results of the "survey".

(If we just ignore for a moment that people can argue on behalf of friends or relatives or people who were merely severely injured could raise their voices)

Is there a name given to this kind of bias / fallacy? I was thinking "selection bias" but the description of that on Wikipedia (https://en.wikipedia.org/wiki/Selection_bias) doesn't seem to quite fit.

Answer 1

The example with the bicycles would seem to fall into the category of survivorship bias (which can apply to more than just physical survival of people but also more general survival of data points past some selection filter that makes you more likely to come across some cases than others, see this xkcd comic for an illustration involving the issue of some people being more likely to get media spotlights than others). More generally, there is also the streetlight effect, a type of observational bias where you only look at samples that share some characteristic that makes them easier to discover, though it's also sometimes understood as a more qualitative problem with the type of evidence used to test a theory, as opposed to a purely statistical fallacy.