Type I error

Definition

A Type I error occurs when a true null hypothesis is incorrectly rejected. It is also known as a false positive.

5 Must Know Facts For Your Next Test

1. A Type I error is denoted by the symbol $\alpha$.
2. The probability of committing a Type I error is called the significance level.
3. A common significance level used in hypothesis testing is 0.05, or 5%.
4. Reducing the significance level decreases the likelihood of making a Type I error but increases the chance of a Type II error.
5. In practical terms, a Type I error might lead to concluding that an effect or difference exists when it actually does not.

Review Questions

• What symbol represents the probability of making a Type I error?
• What happens to the likelihood of a Type II error if you reduce the significance level?
• Provide an example scenario where committing a Type I error could have serious implications.

Related terms

Null Hypothesis: A statement that there is no effect or no difference, often denoted as $H_0$.

Type II Error: Occurs when a false null hypothesis fails to be rejected, also known as a false negative.

Significance Level: The threshold at which we reject the null hypothesis, commonly set at 0.05 or 5%.