Question

In one of the hypothesis study, Robin considers to increase the alpha level. Briefly explain the effect on the Type I and Type II errors together with the probability weather he should reject the null hypothesis.

Answer 1

Type I error is the error of rejecting a null hypothesis when it is actually true. Alpha is the probability of making Type I error. So, if alpha increases, the probability of the Type I error increases.

Type II error is the error of not rejecting a null hypothesis when the alternative hypothesis is true. So, if alpha increases, the probability of the Type II error decreases.

If alpha increases, the probability that the P-value will lie in the critical region increases. So, the probability of rejecting the null hypothesis increases. Type I error is often represented by the Greek letter alpha (α) and a Type II error by the Greek letter beta (β )

In order to graphically depict a Type II, or β, error, it is necessary to imagine next to the distribution for the null hypothesis a second distribution for the true alternative.