Still in Kehan Academy, I met Central Limit Theorem, and found that I have wrong thought about CLT, so write a note here for memory. Following definition is from wikipedia:

In probability theory, the central limit theorem (CLT) states that, given certain conditions, the mean of a sufficiently large number of independent random variables, each with a well-defined mean and well-defined variance, will be approximately normally distributed. The central limit theorem has a number of variants. In its common form, the random variables must be identically distributed. In variants, convergence of the mean to the normal distribution also occurs for non-identical distributions, given that they comply with certain conditions.

Here is the Youtube video maybe useful for reference:

Kehan Academy Central Limit Theorem:

Introduction to the Central Limit Theorem

Central Limit Theorem Part 1

Demonstrating the Central Limit Theorem

Central limit theorem

Central Limit Theorem

Posted by 52nlp