**Type I errors** (**alpha errors, α**) occur when we accept that there is a difference between two experimental groups, when in fact, no difference exists.

The threshold for accepting a type I error is the p-value. The traditionally accepted p-value of 0.05 indicates that the researchers are willing to take a ≤5% chance that the outcome of their data showing a difference between two groups was merely due to chance.

If multiple tests are compared, the risk of type I error increases.

Good statistical technique attempts to keep the risk of type I error as low as possible.