Type II error

Definition

A Type II error occurs when a false null hypothesis is not rejected. This means that a real effect or difference is missed.

5 Must Know Facts For Your Next Test

1. A Type II error is denoted by the symbol $\beta$.
2. The probability of making a Type II error is inversely related to the power of the test (1 - $\beta$).
3. Increasing the sample size typically decreases the probability of making a Type II error.
4. A Type II error can lead to failing to identify a significant finding, which can have serious implications in fields like medicine or business.
5. Type II errors occur more frequently when the effect size is small.

Review Questions

• What does a Type II error represent in hypothesis testing?
• What symbol is used to denote the probability of making a Type II error?
• How does increasing sample size affect the likelihood of committing a Type II error?

Related terms

Type I Error: Occurs when a true null hypothesis is incorrectly rejected, denoted by $\alpha$.

Power of a Test: The probability that the test correctly rejects a false null hypothesis, calculated as 1 - $\beta$.

Null Hypothesis ($H_0$): A statement that there is no effect or no difference, serving as the starting assumption for hypothesis testing.