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lecture_3_23

# lecture_3_23 - Producing data Sampling designs and toward...

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Producing data:  Sampling designs and toward inference IPS chapters 3.2 and 3.3 © 2006 W.H. Freeman and Company

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Objectives (IPS chapters 3.3 and 3.4) Sampling designs; Toward statistical inference Sampling methods Simple random samples Stratified samples Population versus sample Toward statistical inference Sampling variability
Terminology Population - The entire group of individuals in which we are interested but can’t usually assess directly. Sample - The part of the population we actually examine and for which we do have data. Sample survey- survey a sample to draw conclusion about the population. An important kind of observational study.

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Convenience sampling : Just ask whoever is around. Example: “Man on the street” survey (cheap, convenient, often quite opinionated or emotional => now very popular with TV “journalism”) Which men, and on which street? Ask about gun control or legalizing marijuana “on the street” in Berkeley or in some small town in Idaho and you would probably get totally different answers. Even within an area, answers would probably differ if you did the survey outside a high school or a country western bar. Bias: Opinions limited to individuals present. Sampling methods
Voluntary Response Sampling : Individuals choose to be involved. These samples are very susceptible to being biased because different people are motivated to respond or not. Often called “public opinion polls.” These are not considered valid or scientific. Bias: Sample design systematically favors a particular outcome. Ann Landers summarizing responses of readers 70% of (10,000) parents wrote in to say that having kids was not worth it—if they had to do it over again, they wouldn’t.

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lecture_3_23 - Producing data Sampling designs and toward...

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