The probability of committing a Type II Error (β) decreases as:

As the sample size increases, the standard error of the estimator falls (it is proportional to 1/√n). The sampling distributions under the null and under the true alternative become narrower and overlap less. A real effect is therefore easier to detect, and the probability of missing it, β, decreases. Option (A): reducing α makes the test more stringent and shrinks the rejection region, so β increases. This is the trade-off between the two types of error. Options (C) and (E): a larger error variance or larger standard errors make it harder to detect a real effect, so β increases. Option (D): the smaller the true effect, the harder it is to distinguish from zero, so β increases. Hence the correct option is (B).