Type I error
Citation, DOI, disclosures and article data
At the time the article was created Matt A. Morgan had no recorded disclosures.View Matt A. Morgan's current disclosures
At the time the article was last revised Daniel J Bell had no recorded disclosures.View Daniel J Bell's current disclosures
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.