# Chapter 7: Sampling

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bias sample
Some members of the pop. of interest are more likely to be included in the sample
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representative sample
All members of the population have an equal chance of being included in the sample
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self-selection sampling (biased)
Sample has only people who volunteered to participate
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cluster sampling (prob)
Clusters of participants w/i a population are randomly selected and all members are used
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multistage sampling (prob)
2 random samples are selected: a random sample of clusters, then a random sample of people w/i the cluster
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stratified random sampling (prob)
Researchers select demographic categories to represent % in population and uses random selection
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oversampling (prob)
Researcher intentionally overrepresents one or more groups
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oversampling (prob)
Researcher decides that 4% of the population isn't enough to be representative, so they sample 10%
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systematic sampling (prob)
Researcher uses a computer or a random number table to select 2 random numbers
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self-selected, convenience, snowball, purposive, quota
What are the 5 types of non-probability samples?
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snowball sampling (biased)
Researchers find rare individuals and ask participants to bring friends (hard-to-access population)
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quota sampling (biased)
Researcher identifies subsets in the population and sets a target number for each category (80 African Americans, 80 Latinos)
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random sampling
What is most important for enhancing external validity?
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1,000
What sample size is often cited as the optimal balance between accuracy and effort?
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simple random, systematic, stratified, cluster, oversample, multistage sampling
What are the 6 types of probability sampling?
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purposive sampling (biased)
If researchers want to study only certain kinds of people, they recruit only those participants
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frequency claim
Typically, in which type of claim is it most important to have a random sample?
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sampling error (random error)
No 2 samples will be the same; there's always variation
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sample bias (random error)
Sample is systematically bias
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Increase sample size, estimate using stats
How can you reduce sampling error?
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sample bias (constant error)
Selected based on ease or any other systematic difference (self-selection)
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sample isn't representative
Why does sample bias reduce external validity?
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simple random sampling (prob)