While doing hypothesis testing, there is always a possibility of making the wrong decision about your hypothesis; such instances are referred to as ‘errors’. Let’s learn about the different types of errors in hypothesis testing.

There are two types of errors that you might make in the hypothesis testing process: type-I error and type-II error.

- A
**type I-error**, represented by α, occurs when you reject a true null hypothesis.

- A
**type-II error**, represented by β, occurs when you fail to reject a false null hypothesis.

The power of any hypothesis test is defined by 1 – β. The power of the test or the calculation of β is beyond the scope of this course. You can study more about the power of a test at this link.

If you go back to the analogy of the **criminal trial example**, you would find that the probability of making a type-I error is more if the jury convicts the accused even on less substantial evidence. The probability of a type-I error can be reduced if the jury follows more stringent criteria to convict an accused party.

However, reducing the probability of a type-I error may increase the probability of making a type-II error. If the jury becomes very liberal in acquitting people on trial, there is a higher probability of an actual criminal walking free.