Question

Regarding the definition of Type I and Type II error, which of the following is correct?...

Regarding the definition of Type I and Type II error, which of the following is correct?

A) Type I error: Fail to reject the null hypothesis when it is actually false.

B) Type II error: Reject the null hypothesis when it is actually true.

C) The probability of Type I error is equal to the significance level.

D) Neither Type I error nor Type II error can be controlled by the experimenter.

Math   Statistics-And-Probability   
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Answer #1

Solution:- C) The probability of Type I error is equal to the significance level.

A) Type I error: Fail to reject the null hypothesis when it is actually false. Not correct.

A type I error is the rejection of a true null hypothesis.

B) Type II error: Reject the null hypothesis when it is actually true. Not correct.

A type II error is the non-rejection of a false null hypothesis.

C) The probability of Type I error is equal to the significance level. Correct.

The type I error rate or significance level is the probability of rejecting the null hypothesis when it is true. Mostly, the significance level is set to 0.05 (5%).

D) Neither Type I error nor Type II error can be controlled by the experimenter. Not correct.

Type I error can be controlled by experimenter by increasing or decreasing the value of significance level.

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