Question

1. Which of the following will increase the value of the power in a statistical test of hypotheses? (a) Increase the Type II error probability. (b) Increase the sample size. (c) Reject the null hypothesis only if the P-value is smaller than the level of significance. (d) All of the above

2. A significance test gives a P-value of 0.023. This means that the result is statistically significant at (a) both the 0.01 and the 0.05 levels. (b) neither the 0.01 nor the 0.05 levels. (c) the 0.05 level but not at the 0.01 level. (d) the 0.01 level but not at the 0.05 level.

3. In testing hypotheses, if the consequences of rejecting the null hypothesis are very serious, we should (a) use a very large level of significance. (b) use a very small level of significance. (c) insist that the P-value be smaller than the level of significance. (d) insist that the level of significance be smaller than the P-value.

4. The distribution of total body protein in healthy adult men is approximately Normal with standard deviation  = 0.1 kg. A 95% confidence interval for the true mean total body protein of adult men with liver cirrhosis, based on 58 randomly selected adult males with liver cirrhosis, has a margin of error of 0.026 kg. A 90% confidence interval based on the same study

(a) would have the same margin of error. (b) would have a larger margin of error. (c) would have a smaller margin of error. (d) may have a different margin of error, but that would depend on the actual sample mean.

PLEASE ANSWER AND EXPLAIN!

Answer 1

1. Power and Type II error are inversely related, so increasing Type II error will not increase power

As n increases, so does the power of the significance test. This is because a larger sample size narrows the distribution of the test statistic.

Hence answer is b. Increase the sample size