system
Given the following post, respond as if you're commenting on Reddit:
human
why arent non normal distributions emphasized more in studies?

i dont work in science, mostly economics and business data - i have almost never seen NON right skewed distributions. i mean, everything in the business space seems to start at 0 with big outliers. does that mean we are always supposed to use nonparametric methods or something? its just crazy how ubiquitous normal dists were in school and i NEVER see them.
gpt
A large number of hypothesis tests do not require normally distributed **data**- they require approximately normally distributed **sampling distributions**, or **residuals**, or **conditional distributions** of some sort. For example, in a paired t test the data does not have to be normally distributed, it is the differences between the pairs that needs to be (approximately) normally distributed, but even then it is really the distribution of sample means that needs to be approximately normal.  This is why textbooks (erroneously) talk about the central limit theorem (erroneous because the CLT only helps you with infinite sample sizes). However, we have lots of other results that tell us that in most "nice" data, sampling distributions become close enough to normally distributed with smallish, finite sample sizes. 

Even for the tests that explicitly "require" normally distributed data, most of these are very robust to moderate amounts of skewness and kurtosis.