Question

a type 1 error is when
we reject the null hypothesis when it is actually true
we reject the alternative hypothesis when it is actually true
we fail to reject the null hypothesis when it is actually false
we use the incorrect statistical analysis

Explanation:

In hypothesis testing, a Type 1 error (also called a false positive) is defined as rejecting the null hypothesis when it is actually true. The second option refers to a misunderstanding (rejecting alternative when true is not Type 1), the third is a Type 2 error (failing to reject null when it's false), and the fourth is about incorrect analysis, not Type 1 error.

Answer:

We reject the null hypothesis when it is actually true