05, the probability that we commit a type I error is just. If we conduct just one hypothesis test using α =. α: The significance level for a single hypothesis test.When we conduct multiple hypothesis tests at once, we have to deal with something known as a family-wise error rate, which is the probability that at least one of the tests produces a false positive. However, when we conduct multiple hypothesis tests at once, the probability of getting a false positive increases. When we perform one hypothesis test, the type I error rate is equal to the significance level (α), which is commonly chosen to be 0.01, 0.05, or 0.10. We sometimes call this a “false positive” – when we claim there is a statistically significant effect, but there actually isn’t. This is when you reject the null hypothesis when it is actually true.
Whenever you perform a hypothesis test, there is always a chance of committing a type I error.
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