this post was submitted on 13 Mar 2025
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[–] [email protected] 2 points 4 hours ago (1 children)

Can you give me an example of conclusions on one level of detail can't be generalised to another level? I can't quite understand it

[–] [email protected] 2 points 4 hours ago* (last edited 4 hours ago)

Perhaps the textbook example is the Simpson’s Paradox.

This article goes through a couple cases where naively and statically conclusions are supported, but when you correctly separate the data, those conclusions reverse themselves.

Another relevant issue is Aggregation Bias. This article has an example where conclusions about a population hold inversely with individuals of that population.

And the last one I can think of is MAUP, which deals with the fact that statistics are very sensitive in whatever process is used to divvy up a space. This is commonly referenced in spatial statistics but has more broad implications I believe.


This is not to say that you can never generalize, and indeed, often a big goal of statistics is to answer questions about populations using only information from a subset of individuals in that population.

All Models Are Wrong, Some are Useful

  • George Box

The argument I was making is that the NYT will authoritatively make conclusions without taking into account the individual, looking only at the population level, and not only is that oftentimes dubious, sometimes it’s actively detrimental. They don’t seem to me to prove their due diligence in mitigating the risk that comes with such dubious assumptions, hence the cynic in me left that Hozier quote.