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]