The answer is true .
A smaller value of α is more effective in rejecting the null hypothesis. In hypothesis testing, the significance level (α) is a predetermined criterion used to determine whether there is enough evidence to reject the null hypothesis. When α is set to a small value, the criteria for rejecting the null hypothesis are more stringent.
This means that strong evidence is needed to establish the meaning and reject the null hypothesis.
Thus, a small α reduces the probability of a Type I error (reject the null hypothesis) but increases the probability of a Type II error (reject the null hypothesis if false). So when α is small, it is very easy to reject the null hypothesis when there is enough evidence to support the alternative hypothesis.