A Type I error is defined as the incorrect rejection of a true null hypothesis. Therefore, the statement a is true: ‘Type I error is the probability of rejecting the null when it is true.’
On the other hand, statement b is false: ‘Type I error is the probability of not rejecting the null when it is true.’ In fact, this describes the correct decision when the null hypothesis is true, not an error.
Lastly, statement c is also false as it appears to be incomplete: ‘Type II error is the probability of rejecting the null.’ A Type II error actually refers to the failure to reject a false null hypothesis, which means we made an error by not identifying a true effect when one exists.
In summary, only statement a is true.