key term - Type II error

Definition

A Type II error occurs when the null hypothesis is not rejected even though it is false. This results in a failure to detect an effect that is actually present.

5 Must Know Facts For Your Next Test

1. Type II error is also known as a 'false negative' or 'beta error'.
2. The probability of committing a Type II error is denoted by $\beta$.
3. Reducing the significance level ($\alpha$) can increase the likelihood of a Type II error.
4. Type II errors are influenced by sample size, effect size, and variability within the data.
5. Power of a test (1 - $\beta$) measures its ability to avoid Type II errors.

Review Questions

Related terms

Type I Error:

An incorrect rejection of a true null hypothesis, also called a 'false positive' or 'alpha error'.

$\alpha$ (Alpha): The significance level in hypothesis testing, representing the probability of making a Type I error.

$\beta$ (Beta): The probability of making a Type II error, failing to reject a false null hypothesis.