What are Type I and Type II errors?

A Type I error is when the null hypothesis is incorrectly rejected. The null hypothesis states that there is no relation between the independent variable and the dependent variable. This means the experiment has found an effect that isn’t there. A good way to remember this is to compare it to a ‘false positive’ on a pregnancy test. A Type II error is when the null hypothesis is incorrectly accepted. This means no effect has been found when there was an effect. This is like a ‘false negative’ on a pregnancy test. To remember which is which, you can remember that in Type 1 the null hypothesis is ‘rejected’ (1 word) and in Type 2 it is ‘not rejected’ (2 words).