Question

Explain what Type I and Type II errors are.

Answer 1

Type 1 and type 2 errors that can be made while performing a hypothesis test.

Type 1 error:

Type 1 error is the probability of rejecting the null hypothesis when it should not be rejected. This happens the significance level percentage of times. It is a false negative.

Think of the normal distribution. The area under the curve of a normal distribution is equal to 1. The values close to the mean are most likely to occur, and values away from the mean are less likely to occur. Thus, we set a significance level. This is the percentage of time we will reject the null hypothesis. These values are always taken from the extreme ends of the normal distribution, as these values are least likely to occur. Thus, the significance level of times, you will reject the null hypothesis, when it should not have been rejected.

Type 2 error:

Type 2 error is the probability of failing to reject the null hypothesis when it should be rejected. It is a false positive.

Generally, this means that the sample comes from another distribution which overlaps our distribution. So, we fail to reject the null hypothesis, but it should have been rejected.

Please let me know if you have any other doubts related to errors. This is a pretty open ended question, so please let me know if you do not understand the answer. Happy learning!