For Exercise 23.1, see page 554; for Exercise 23.2, see page 557.
23.3 Finding statistical significance. If we conduct 100 hypothesis tests at the 5% level, how many of them would we expect to be statistically significant even if none of them were?
(a) 0
(b) 5
(c) 95
(d) 100
23.4 Width of a confidence interval. Suppose that the length of a confidence interval is 0.06 when the sample size is 400. To decrease the length of the confidence interval to 0.03, we should take a sample of size
(a) 100.
(b) 200.
(c) 800.
(d) 1600.
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23.5 Practically significant? A new blend of gasoline costs $1.00 more per gallon than regular gasoline. Tests have shown that gas mileage with the new blend is statistically significantly higher than it is with regular gasoline. The P-value was 0.004. A report about these results goes on to say that the new blend of gasoline increases gas mileage by 2 miles per gallon. Are these results practically significant?
(a) No, because the P-value is small.
(b) No, because a 2 mile-
(c) Yes, because the P-value is small.
(d) Yes, because a 2 mile-
23.6 Practically significant? Brook conducted a study for a clothing company to determine if a rewards program caused customers to spend more. Brook found statistically significant results, with a P-value of 0.012. The average amount spent per order before the rewards program was $100, while the average amount spent per order after the rewards program was $223. Are these results practically significant?
(a) No, because the P-value is small.
(b) No, because an average increase of $123 per order is probably too small.
(c) Yes, because the P-value is small.
(d) Yes, because an average increase of $123 per order is more than twice the average amount spent per order before the rewards program.
23.7 Sacred significance level. A researcher decided prior to conducting research to use a 1% level of significance. The researcher finds a P-value of 0.027. Is it okay for the researcher to change the significance level to 5% to have statistically significant results?
(a) No, because the significance level is set beforehand and should not be changed after the P-value has been calculated.
(b) No, because the researcher should redo the study with a larger sample size to make sure to get significant results.
(c) Yes, because it is okay to change the significance level after the P-value is calculated.
(d) Yes, because the researcher should have chosen the 5% level in the first place.