In a similar manner, consider the case where the hypothesis is false but you determine (in error) that it is true. This is called a Type II error and will be denote the probability of a Type II error by \(\beta\text{.}\) Again, your goal is to make the risk of a Type II error smaller and therefore want \(\beta\) to be as small as possible.