The researcher is interested to know if policy A (new) is more effective than policy B (old). Frame the hypothesis and describe what each error would represent in terms of reality and conclusion.

Null hypothesis: Policy B remains more effective than policy A.

Alternate hypothesis: Policy A is more effective than policy B.

Step-by-step explanation:

Remember, a hypothesis is a  usually tentative (temporary until tested) assumption about two variables– independent and the dependent variable.

We have two types of hypothesis errors:

1. A type I error occurs when the null hypothesis (H0) is wrongly rejected.

That is, rejecting the assumption that policy B remains more effective than policy A when it is actually true.

2. A type II error occurs when the null hypothesis H0, is not rejected when it is actually false. That is, accepting the assumption that policy B remains more effective than policy A when it is actually false.