The only available option is to minimize the probability of committing this type of statistical error. Similar to the type I error, it is not possible to completely eliminate the type II error from a hypothesis test. The rate of a type II error (i.e., the probability of a type II error) is measured by beta (β) while the statistical power is measured by 1- β. This means that the higher power of a statistical test, the lower the probability of committing a type II error. The type II error has an inverse relationship with the power of a statistical test. The type II error is also known as a false negative. In other words, it causes the user to erroneously not reject the false null hypothesis because the test lacks the statistical power to detect sufficient evidence for the alternative hypothesis. Saving Earth Britannica Presents Earth’s To-Do List for the 21st Century.In statistical hypothesis testing, a type II error is a situation wherein a hypothesis test fails to reject the null hypothesis that is false.Britannica Beyond We’ve created a new place where questions are at the center of learning.

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Type 2 error