Question

question 3 suppose the results indicate that the null hypothesis should be rejected; thus, it is possible that a type i error has been committed. given the type of error made in this situation, what could researchers do to reduce the risk of this error? a. increase the sample size. b. choose a 0.01 significance level instead of a 0.05 significance level.

Explanation:

A type - I error occurs when the null hypothesis is rejected when it is actually true. The significance level $\alpha$ is the probability of making a type - I error. By choosing a lower significance level (from 0.05 to 0.01), we reduce the probability of rejecting the null hypothesis when it is true. Increasing the sample size reduces the probability of a type - II error, not a type - I error.

Answer:

B. Choose a 0.01 significance level instead of a 0.05 significance level.