1. If all else remains the same, which of these will make a confidence interval for a proportion wider? I. Increase the confidence level. IL Increase the sample size. Ill.Increase the margin of error. A. I only B. Ill only C. I and Ill D. II and Ill E. I, Il, and Ill 2. The power of a test is DO NOT DO A. the probability of rejecting the null hypothesis. B. the probability of rejecting the allemative hypothesis C. the probability of failing to reject the null hypothesis. D. the probability of failing to reject the alternative hypothesis. E. the probability that you will make the correct decision. 3. A recent poll reported that about 60% of U.S. adults consume moderate amounts of chocolate, with a margin of error of 13%%. Which of these best describes the parameter that is estimated by the interval 57% to 63%? A. It is the percentage of the U.S. adults in this sample who consume moderate amounts of chocolate. B. It is the percentage of all U.5. adults who consume moderate amounts of chocolate. C. It is the hypothesized percentage of U.5. adults who consume moderate amounts of chocolate. D. It is any reasonably likely percentage of U.5. adults who consume moderate amounts of chocolate. E. It is the probability of capturing the true proportion of U.S. adults who consume moderate amounts of chocolate in this confidence interval. 4. Which of these statements is nof true for a researcher who is using standard statistical methods in a test of significance? A. A researcher who rejects a true null hypothesis has committed a Type I error. B. A researcher who rejects the null hypothesis has computed a test statistic that is large in absolute value. C. A researcher who rejects the null hypothesis has computed a P-value that is large in value. D. When the null hypothesis is true, the probability of making a Type I error is equal to the significance level. E. Increasing the sample size has no effect on the probability of making a Type I error