目录

假设检验中的两类错误

Two type of errors in hypothesis testing

没有效应,H0正确 存在效应,H0错误
拒绝H0 I类错误 正确
接受H0 正确 II类错误
false effect, H0is correct real effect, H0is wrong
Reject H0 Type I error Correct
Accept H0 Correct Type II error

两种错误,即:

The two types of errors are:

显著性水平

level of significance

在科学研究中,我们常常采取保守的策略,设定一个可接受的α水平来尽量减少I类错误。该α水平称为显著性水平。它规定了当虚无假设正确时,样本结果非常不可能出现的概率值。心理学研究中,α通常为0.05。 1) 2)

1)
《心理学名词》:显著性水平是指在统计推断中,观察值或假设检验统计量落入估计区间或拒绝域的概率。是统计推断错误的概率指标。
2)
APA Dictionary: In SIGNIFICANCE TESTING, a fixed probability of rejecting the NULL HYPOTHESIS of no effect when it is in fact true. It is set at some value, usually .001, .01, or .05, depending on the consequences associated with making a TYPE I ERROR. When a particular effect is obtained experimentally, the PROBABILITY LEVEL (p) associated with this effect is compared to the significance level. If the p value is less than the a level, the null hypothesis is rejected. Small p values suggest that obtaining a statistic as extreme as the one obtained is rare and thus the null hypothesis is unlikely to be trae. The smaller the a level, the more convincing is the rejection of the null hypothesis.