Question

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?
○ choose a 0.01 significance level, instead of a 0.05 significance level.
○ increase the sample size.

Explanation:

A Type I error is rejecting a true null hypothesis. The significance level ($\alpha$) is the probability of making a Type I error. A lower significance level reduces the probability of Type I error. Increasing sample size affects Type II error (failing to reject a false null hypothesis) more directly.

Answer:

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