Chi-Square Statistic/Distribution

1、What is a Chi Square Test?

卡方检验有两种类型。两者使用卡方统计量和分布的目的不同。

第一种：卡方拟合优度检验确定样本数据是否与总体匹配。(这里不介绍)

第二种：独立性的卡方检验比较列联表中的两个变量，看看它们是否相关。在更一般的意义上，它测试分类变量的分布是否不同。

　　　　一个非常小的x平方分布测试统计量意味着您观察到的数据非常适合您的预期数据。换句话说，之间有关系。

　　　　非常大的x平方分布测试统计量意味着数据不太适合。换句话说，之间没有关系。

There are two types of chi-square tests. Both use the chi-square statistic and distribution for different purposes:A chi-square goodness of fit test determines if a sample data matches a population. For more details on this type, see: Goodness of Fit Test.
A chi-square test for independence compares two variables in a contingency table to see if they are related. In a more general sense, it tests to see whether distributions of categorical variables differ from each another.
　　　　A very small chi square test statistic means that your observed data fits your expected data extremely well. In other words, there is a relationship.
　　　　A very large chi square test statistic means that the data does not fit very well. In other words, there isn’t a relationship.

https://www.statisticshowto.datasciencecentral.com/probability-and-statistics/chi-square/

原文地址：https://www.cnblogs.com/djx571/p/10205020.html