Final answer:
Without additional statistical information, evaluating β, the probability of a Type II error, is not possible. The correct answer is 'd. Insufficient data'. Also, when performing hypothesis testing, decisions are based on the p-value in comparison to the designated alpha level.
Step-by-step explanation:
In hypothesis testing, β (beta) is the probability of making a Type II error, which occurs when the null hypothesis is not rejected even though it is false. The question asked, 'Evaluate β for the alternatives μ = 4970 and μ = 4960', requires additional context such as the standard deviation, sample size, actual mean under the alternative hypothesis and distribution types to provide a proper calculation for β. Without this information, it is impossible to calculate and evaluate β. Therefore, the answer is 'd. Insufficient data'.
To reach conclusions in hypothesis testing, information about the significance level (α), p-value, and whether the test is one-tailed or two-tailed is essential. In some of the provided reference information, it mentions 'alpha = 0.05' which commonly represents the significance level. If the p-value is less than the significance level, the null hypothesis is rejected. Otherwise, we do not reject the null hypothesis, indicating insufficient evidence against it.