Question

Explain Type 1 & Type 2 errors.

Answer 1

A type I error is the rejection of a null hypothesis when it's true, while a type II error is the non-rejection of a false null hypothesis.

A type I error is also known as false positive. In other words, this is the error of accepting an alternative hypothesis.

A type II error is also known as false negative. In other words, this is the error of failing to accept an alternative hypothesis when you don't have adequate power.

Consequences of a type 1 and type 2 Error:

A type 1 error will bring in a false positive. This means that you will wrongfully assume that your hypothesis testing has worked even though it hasn’t and type 2 errors can lead to false assumptions and poor decision making that can result in lost sales or decreased profits.