Chapter 8 summary

Chapter 8 summary - Failure to use random sampling often...

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Chapter 8 A sample survey selects a sample from the population of all individuals about which we desire information. We base conclusions about the population on data from the sample . It is important to specify exactly what population you are interested in and what variables you will measure. The design of a sample describes the method used to select the sample from the population . Random sampling designs use chance to select a sample . The basic random sampling design is a simple random sample (SRS). An SRS gives every possible sample of a given size the same chance to be chosen. Choose an SRS by labeling the members of the population and using random digits to select the sample . Software can automate this process . To choose a stratified random sample , classify the population into strata, groups of individuals that are similar in some way that is important to the response. Then choose a separate SRS from each stratum.
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Unformatted text preview: Failure to use random sampling often results in bias , or systematic errors in the way the sample represents the population . Voluntary response samples , in which the respondents choose themselves, are particularly prone to large bias . In human populations , even random samples can suffer from bias due to undercoverage or nonresponse , from response bias , or from misleading results due to poorly worded questions. Sample surveys must deal expertly with these potential problems in addition to using a random sampling design. Most national sample surveys are carried out by telephone,using random digit dialing to choose residential telephone numbers at random. Call screening is increasing nonresponse to such surveys, and the rise of cell-phone-only households is increasing undercoverage ....
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