Suppose a study found a strongly statistically significant relationship between two variables. The ...

Suppose a study found a strongly statistically significant relationship between two variables. The test statistic and the p-value for this study __________ (choose: would, would not) provide information about the magnitude of the effect.
 Fill in the blank(s) with correct word

Q. 2

Which of the following statements must be true regarding a p-value of .0001?
 a. Since this p-value is so small, the results will have practical as well as statistical significance.
  b. The magnitude of the effect found in this study must have been huge.
  c. There must have been very little variability in the results of this study.
  d. None of the above.

Q. 3

Suppose you read the following headline: Taking an aspirin a day can cut your risk of heart attack by almost half Suppose the news report goes on to tell you that the research is based on a very large well-designed randomized experiment with a p-value less than 0.0001 . Assume this information is technically correct, given the results of the study. Which of the following statistics could actually represent the results of this study?
 a. The rates of heart attack were 9.4 per thousand for the aspirin group and 17.1 per thousand for the placebo group (non aspirin).
  b. 94 people in the aspirin group had a heart attack, compared to 171 people in the non-aspirin group.
  c. The risk of a heart attack for the aspirin group was 45 of the risk of a heart attack for the non-aspirin group.
  d. Any of the above could have been possible.

Q. 4

What information can a confidence interval provide that a p-value alone cannot?
 a. The direction of a difference or relationship, if one is concluded to exist.
  b. The amount of variability in the results.
  c. The actual size of an effect such as relative risk of heart attacks.
  d. All of the above.

Q. 5

Suppose a researcher examined a relationship between taking aspirin every day (yes/no) and the incidence of a heart attack (yes/no). The sample data showed that those taking aspirin had a lower chance of incidence of heart attack. A chi-square test on the data collected resulted in a p-value less than 0.0001 . The data were collected in a well-designed randomized experiment. Which of the following conclusions is appropriate?
 a. The probability that there is a relationship between the two variables is more than 99.99.
  b. For this population, taking aspirin reduces the risk of heart attack.
  c. Heart attacks happened much more often for the non-aspirin takers than the aspirin takers.
  d. All of the above conclusions are appropriate.

Q. 6

Explain why it is important to not only be aware of the proportion of people who were in favor or opposed to something, but the proportion of undecideds as well.