[resource record] as a self-study record of programmers on Chi square distribution / detection, t distribution / detection, F distribution / detection in statistics

As a programmer , The knowledge of statistics is limited , I spent some time reading various materials tonight , Try to solve a few concepts that have been unclear for a long time ： Chi square distribution & Chi square test ,t Distribution &t testing ,f Distribution &f testing .

First of all, I found that the best order to learn these concepts is , First look at Chi square test 、 Chi square distribution , Look again t and f.

1. chi-square

Application of chi square distribution ：https://www.cnblogs.com/baiboy/p/tjx11.html

This is a very good article , Use two examples , About chi square detection , And how to check the table （ That is, the Chachi square distribution density function ） To determine whether or not To accept or reject H0 hypothesis . This article made me realize , In general procedure , Found p-value, Is the chi square density function “ The tail ” The area of . And this is for t testing 、f Detection is the same , Here's the picture ：

2. t testing / Distribution ,f testing / Distribution

Easy to understand t testing 、f testing ：https://blog.csdn.net/cyydjt/article/details/81056080

In linear regression t testing 、f testing ：https://blog.csdn.net/a8131357leo/article/details/80300336

t Distribution 、f Distribution ：https://blog.csdn.net/anshuai_aw1/article/details/82735201

Macro, , be used t The detection of distribution is t testing , be used f The detection of distribution is f testing , example ：ANOVA test It's a kind of f test（An ANOVA is a specific type of procedure that produces an F-statistic, because it tests the ratio between systematic variance and error-variance.）.

I think for programmers , Most encountered t testing ,f The place of detection , Is to use linear regression （linear regression） It's time . Then think about it , In fact, the application in linear regression , It seems to fit the description in popular understanding , And as shown above, chi square is distributed in Chi square detection Same relationship ,t testing 、f testing It depends on t Distribution and f The distribution of the .

3. ANOVA test

Record an English blog that I feel speaks well ：

https://blog.minitab.com/blog/adventures-in-statistics-2/understanding-analysis-of-variance-anova-and-the-f-test

https://www.quora.com/What-is-the-difference-between-the-F-test-and-ANOVA

above , That's all , I hope to have a chance to deepen my understanding in the future , Come back and add .