统计分析中Type I Error与Type II Error的区别
在统计分析中，经常提到Type I Error和Type II Error。他们的基本概念是什么？有什么区别？
下面的表格显示 between truth/falseness of the null hypothesis and outcomes of the test
Type I error：
false positive,
Testing shows that something is present, but it is not. Incorrect detection of something.
Type II error:
false negative,
Testing shows that something is not present, but in fact it is present. Fail to detect something.
In statistical hypothesis testing, a type I error is the incorrect rejection of a true null hypothesis (a "false positive"), while a type II error is the failure to reject a false null hypothesis (a "false negative").