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In statistical hypothesis testing, a Type I error consists of rejecting a null hypothesis that is true, in other words finding a result to have statistical significance when this has in fact happened by chance. A test with high specificity will have fewer Type I errors. The symbol for the probability of a Type I error is α (alpha) and is sometimes described as the size of the test.
See also Type II error.
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