The probability we choose puts an upward bound on the probability of falsely rejecting the null hypothesis. Falsely rejecting the null hypothesis is referred to as Type I error. Failing to reject the null hypothesis when in fact the alternative hypothesis is true is referred to as Type II error. We usually set the probability of Type I error at some low level, such as 5 percent. Holding the sample size constant, the lower we set the probability of a Type I error, the greater the probability of a Type II error.