CH+9 - Producing data: experiments BPS chapter 9 2006 W. H....

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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 called subjects. The explanatory variables in an experiment are often called factors . A treatment is any specific experimental condition applied to the subjects.
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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 ? •The factors/treatments ? •And the response variable ?
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How to experiment badly Subjects Treatment Measure response Field experiments and experiments with human subjects are exposed to more variable conditions and deal with more variable subjects. A simple design often yields worthless results because of confounding with lurking variables.
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3 Principles of experimental design 1. Control the effects of lurking variables on the response, most simply by comparing two or more treatments. 1.
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This note was uploaded on 04/15/2008 for the course MATH 1070 taught by Professor Akbas during the Spring '08 term at Georgia State University, Atlanta.

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CH+9 - Producing data: experiments BPS chapter 9 2006 W. H....

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