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Type I: rejecting the null hypothesis when it is true. Type II: not rejecting the null hypothesis when the alternative is true.

Type I and Type II errors:

  • Type I error, also known as a “false positive”: the error of rejecting a null hypothesis when it is actually true. In other words, this is the error of accepting an alternative hypothesis (the real hypothesis of interest) when the results can be attributed to chance. Plainly speaking (when the null hypothesis asserts there is no difference), it occurs when we conclude there is a difference when in truth there is none.

  • Type II error, also known as a "false negative": the error of not rejecting a null hypothesis when the alternative hypothesis is the true state of nature. In other words, this is the error of failing to reject the null hypothesis. Plainly speaking, it occurs when we do not conclude there is a difference when in truth there is one.

Reference: http://www.stat.berkeley.edu/users/hhuang/STAT141/Lecture-FDR.pdf