Author Question: How does sample size affect the decision to reject or failure to reject of a null hypothesis? ... (Read 137 times)

kwoodring · **on:** Jun 24, 2018

How does sample size affect the decision to reject or failure to reject of a null hypothesis?

What will be an ideal response?

Question 2

Which of the following, if true, would suggest that Reuben reneged?

A) He chose the counter with the least number of customers to place his order.
B) He canceled his order and decided to find another food joint where he would not have to wait long.
C) He exchanged his turn with an old gentleman after him who had been assigned the waiting number 28.
D) He tried to exchange his turn with a lady who would be serviced ahead of him, citing a personal emergency.

ktidd · **Reply #1 on:** Jun 24, 2018

Answer to Question 1

The null hypothesis has the status of a maintained hypothesisone held to be trueunless the data contain strong evidence to reject the hypothesis. By setting the significance level, at a low level, we have a small probability of rejecting a true null hypothesis. When we reject a true null hypothesis, the probability of error is the significance level, . But if there is only a small sample, then we will reject the null hypothesis only when it is wildly in error. As we increase the sample size, the probability of rejecting a false null hypothesis is increased. But failure to reject a null hypothesis leads to much greater uncertainty because we do not know the probability of the Type II error. Thus, if we fail to reject, then either the null hypothesis is true or our procedure for detecting a false null hypothesis does not have sufficient powerfor example, the sample size is too small.

Answer to Question 2

B