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It's just trying to assume normal distribution when it's not normal. Modern science rely so much on that distribution that i actually whether they have overesti

• Jweb_Guru 2y ago
  While it is true that not all distributions are normal, many distributions are approximately normal (or at least, normal in some sensible space that maps onto the actual collected data). IMO the amount of ink spilled on the idea that science is fundamentally flawed because distributions aren't always normal is probably too high (especially among non-statisticians), and frankly that's not where statistical analyses usually go wrong. A much larger problem (that has nothing to do with the ultimate shape of the distribution) is stuff like postselecting from a set of plausible models until you find one that finds significant results, and claiming that was what you intended to measure all along (this is why it's important to consider stuff like hyperpriors, much moreso than lack of normality).
• _yb2s 2y ago
  Yes, this is the actual issue- assuming a normal distribution in cases that are not normally distributed. People also even leave off the standard deviation, and seem to be mentally thinking of the average as a point rather than considering even the “width” of the normal distribution- so the overemphasis of the average even causes people to misunderstand things that really are normally distributed.