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Kelly001 · 2021年12月06日

Type I and Type II error的理解

NO.PZ2018062016000130

问题如下:

Which of the following statements on the power of a test is most correct?

选项:

A.

The power of a test is the probability of making a Type I error.

B.

The power of a test is the probability of not making a Type II error.

C.

The power of a test has a negative effect with the sample size.

解释:

B is correct. The power of a hypothesis test is the probability of not making a Type II error and it has a positive effect with the sample size.

表格中的significance level = P 和 power of test =1-P, 这两个P不是同一个数据吧? Type I error =P1, Type II error= P2 是这么理解吗?

1 个答案

星星_品职助教 · 2021年12月06日

同学你好,

不是一个概率。

significance level =P(Type I error),即你描述的P1

power of test的概率=1 - P(Type II error),即你描述的P2。P2和P(Type I error)不发生直接联系。

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