If you wish to conduct a hypothesis test using a small significance level , you should have a large sample size to avoid committing a Type II error.

Question

If you wish to conduct a hypothesis test using a small significance level   , you should have a large sample size to avoid committing a Type II error.

hataw nasri · Accepted Answer

Final Answer : False, Explanation :  A small significance level means that you have a lower tolerance for accepting the null hypothesis, and thus require stronger evidence to reject it. This does not necessarily have any relation to the probability of committing a Type II error, which is the probability of failing to reject the null hypothesis when it is false (i.e. accepting a false null hypothesis). The probability of committing a Type II error depends on factors such as sample size, effect size, and variability, and cannot be reduced simply by using a smaller significance level. In fact, using a smaller significance level can increase the probability of committing a Type II error, because it reduces the power of the test (i.e. the ability to detect a true effect). Therefore, having a large sample size is generally recommended to increase the power of the test and reduce the risk of Type II error, regardless of the significance level.

If you wish to conduct a hypothesis test using a small significance level , you should have a large sample size to avoid committing a Type II error.

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