# Type I and type II errors

In statistics, type I and type II errors are errors that happen when a coincidence occurs while doing statistical inference, which leads to one making the wrong conclusion. One makes a Type I error when the original hypothesis is rejected, when it is actually true. Conversely, one makes a Type II error when the original hypothesis is accepted, when it is actually false. The probability of type I error is often written as ${\displaystyle \alpha }$, while the probability of type II error is written as ${\displaystyle \beta }$.[1][2][3]

## References

1. "Greek/Hebrew/Latin-based Symbols in Mathematics". Math Vault. 2020-03-20. Retrieved 2020-10-03.
2. "5. Differences between means: type I and type II errors and power | The BMJ". www.bmj.com. Retrieved 2020-10-03.
3. Banerjee, Amitav; Chitnis, U. B.; Jadhav, S. L.; Bhawalkar, J. S.; Chaudhury, S. (2009). "Hypothesis testing, type I and type II errors". Industrial Psychiatry Journal. 18 (2): 127–131. doi:10.4103/0972-6748.62274. ISSN 0972-6748. PMC 2996198. PMID 21180491.