Toward that end, let’s consider the case where the hypothesis is true but you determine (in error) that it is false. This is called a Type I error and we will designate the probability of this error by \(\alpha\text{.}\) To lower the risk of a Type I error, you will want to make \(\alpha\) smaller. In general, \(\alpha\) is also called "the significance level" with \(\alpha = 0.05\) a common choice with 0.01 and 0.10 also sometimes used. In general, any value between 0 and 1 is ok but large values mean large likelihood for error so choosing a value closer to 0 is preferred.