[MR4D]

Respectfully, I find that people who are not statisticians overwhelming disagree with your point on which should be taught first.

Bayesian is a natural order of inference for people. The whole concept of the black swan ("all swans are white") proves this out.

Frequentist statistics is much less intuitive to people.

My preference is for people to be able to use some statistics, and Bayesian gets them productive faster.

[tel]

Frequentist statistics is often pretty poorly taught. Ideas like likelihood, modeling, and optimization underly the mechanics of both worlds. There's a big obsession with testing, but the Neyman Pearson testing framework is sound an intuitive.

Bayesian statistics gets a big boost because it's usually taught as a system instead of as a recipe book.

[codesushi42]

I would argue that the problem with frequentist statistics is that it aligns with humans' flawed intuition of how randomness works. People are inherently obsessed with finding patterns to support their hypotheses.

The problem is that what we perceive as random and extremely unlikely events are in fact much more probable than what we estimate from using Gaussian methods. And the frequentist approach helps to create this distortion by ignoring black swans.

Here's a great video demonstrating how people tend to misunderstand randomness: https://youtu.be/tP-Ipsat90c