type I error

How it is used

Its probability is set by the significance level α, so with α = .05 you accept a 5% risk of a Type I error in each test. Running many tests without correction inflates the overall Type I error rate. Usually written with a capital T and a Roman numeral: Type I.

Example sentences

1. A Type I error here would mean approving a drug that doesn't actually work.

2. The Bonferroni correction keeps the overall Type I error rate at or below 5%.

Common collocations

• Type I error rate
• commit a Type I error
• risk of a Type I error
• control the Type I error rate

Related terms

• type II errorFailing to reject a null hypothesis that is actually false, in other words missing an effect that really exists; a false negative.
• significance levelThe threshold, chosen before a test, below which a p-value is treated as statistically significant; it is also the accepted risk of a Type I error.
• null hypothesisThe default claim in a statistical test that there is no effect, no difference or no relationship; the test checks whether the data give enough evidence against it.
• post hoc testA follow-up test run after a significant overall result, such as an ANOVA, to find out exactly which groups differ from each other.
• statistical powerThe probability that a test will detect an effect when a real effect of a given size exists; it equals one minus the probability of a Type II error.

More terms: Hypothesis Testing

• hypothesis
• p-value
• statistical significance
• alternative hypothesis
• reject the null hypothesis
• t-test
• chi-square test
• ANOVA
• degrees of freedom
• two-tailed test
• assumption
• nonparametric test