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Chapter09

The Basic Practice of Statistics (Paper) & Student CD

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Producing data: experiments BPS chapter 9 © 2006 W. H. Freeman and Company
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Objectives (BPS chapter 9) Producing data: experiments Experiments How to experiment badly Randomized comparative experiments The logic of randomized comparative experiments Cautions about experimentation Matched pairs and other block designs
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Terminology The individuals in an experiment are the experimental units. If they are human, we call them subjects. The explanatory variables in an experiment are often called factors . A treatment is any specific experimental condition applied to the subjects. If an experiment has several factors, a treatment is a combination of specific values of each factor. The factor may be the administration of a drug. One group of people may be placed on a diet/exercise program for 6 months (treatment), and their blood pressure (response variable) would be compared with that of people who did not diet or exercise.
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If the experiment involves giving two different doses of a drug, we say that we are testing two levels of the factor. A response to a treatment is statistically significant if it is larger than you would expect by chance (due to random variation among the subjects). We will learn how to determine this later. In a study of sickle cell anemia, 150 patients were given the drug hydroxyurea, and 150 were given a placebo (dummy pill). The researchers counted the episodes of pain in each subject. Identify: •The subjects (patients, all 300) •The factors/treatments (hydroxyurea and placebo) •And the response variable (episodes of pain)
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Apply your knowledge Go to page 215 and work on the following problems: 9.1 Internet telephone calls 9.2 Growing in the shade 9.3 Improving adolescents’ habits
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How to experiment badly Subjects Treatment Measure response In a controlled environment of a laboratory (especially if human subjects are not being used), a simple design like this one, where all subjects receive the same treatment, can work well.
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