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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
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)
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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