STATISTICS IN SUMMARY
Chapter Specifics
• Because the placebo effect is strong, clinical trials and other experiments with human subjects should be double-blind whenever this is possible.
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• The double-blind method helps achieve a basic requirement of comparative experiments: equal treatment for all subjects except for the actual treatments the experiment is comparing.
• The most common weakness in experiments is that we can’t generalize the conclusions widely. Some experiments apply unrealistic treatments, some use subjects from some special group such as college students, and all are performed at some specific place and time. We want to see similar experiments at other places and times confirm important findings.
• Many experiments use designs that are more complex than the basic completely randomized design, which divides all the subjects among all the treatments in one randomization. Matched pairs designs compare two treatments by giving one to each of a pair of similar subjects or by giving both to the same subject in random order. Block designs form blocks of similar subjects and assign treatments at random separately in each block.
• The big ideas of randomization, control, and adequate numbers of subjects remain the keys to convincing experiments.
In Chapter 5, we learned that well-designed randomized comparative experiments provide a sound basis for determining if a treatment causes changes in a response. In the real world, simple randomized comparative experiments don’t solve all the difficulties of experimenting. The placebo effect and researchers’ expectations can introduce biases that undermine our conclusions. Just as samples suffer from nonresponse, experiments suffer from uncooperative subjects. Some subjects refuse to participate; others drop out before the experiment is complete; others don’t follow instructions, as when some subjects in a drug trial don’t take their pills. More complex designs and techniques, some of which were discussed in this chapter, are used to overcome real-world difficulties. We must pay careful attention to every aspect of an experiment to ensure that the conclusions we make are valid. And when reading about the results of experiments, you should use the ideas provided in this chapter to assess the quality of the conclusions.
CASE STUDY EVALUATED Use what you have learned in this chapter to evaluate the Case Study that opened the chapter. Start by reviewing the information on page 117. You can also read the EESEE story “Is Caffeine Dependence Real?” for additional information. Then answer each of the following questions in complete sentences. Be sure to communicate clearly enough for any of your classmates to understand what you are saying.
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First, here are the results of the study. The number of subjects who showed withdrawal symptoms during the period in which they took capsules that did not contain caffeine and the magnitude of their symptoms were considered statistically significant.
1. Explain what the phrase “statistically significant” means.
2. Explain why the researchers gave subjects capsules with a fake substance rather than just having them take nothing during one of the periods.
3. What advantage is gained by having subjects take both a capsule with caffeine and a capsule with a fake substance rather than having some of the subjects just take a capsule with caffeine and the remaining subjects just take a capsule with a fake substance?
Online Resources
•The Snapshots video Introduction to Statistics describes real-world situations for which knowledge of statistical ideas is important.