Chapter 7: Estimating the frequency of behaviors and beliefs Flashcards

1
Q

population

A

the entire set of people a researcher is interested in

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2
Q

census

A

a set of observations that includes all members of the population of interest

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3
Q

biased (unrepresentative) sample

A

some members of the population of interest have a much higher probability than other members of being included in the sample

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4
Q

unbiased (representative) sample

A

all members of the population have an equal and known chance of being included in the sample

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5
Q

ways a sample could be biased

A
  • researchers might only study those who they can contact conveniently
  • researchers might only study those who volunteer to respond
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6
Q

convenience sampling

A

a biased sampling technique in which researchers choose a sample based on those who are easiest to access and are readily available

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7
Q

self-selection

A

a from of sampling bias that occurs when a sample contains only participants who volunteer to participate

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8
Q

probability (random) sampling

A

every member of the population of interest has an equal and known chance of being selected for the sample

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9
Q

simple random sampling

A

the most basic form of probability sampling in which the sample is chosen completely randomly from the population of interest

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10
Q

systematic sampling

A

a probability sampling technique in which the researcher uses a randomly chosen number N and counts for every Nth member of a population to achieve a sample

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11
Q

cluster sampling

A

a probability sampling technique in which clusters of participants within the population of interest are selected at random, followed by data collection from all individuals in each cluster

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12
Q

multistage sample

A

a probability sampling technique involving at least 2 stages: a random sample of clusters, followed by a random sample of people within the selected clusters

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13
Q

stratified random sampling

A

a form of probability sampling in which the researcher identifies particular demographic categories or strata, and then randomly selects individuals within each category, proportionate to their assumed membership in the population

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14
Q

oversampling

A

a form of probability sampling, a variation of stratified random sampling in which the researcher intentionally overrepresents one or more groups

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15
Q

random assignment

A

researchers randomly assign participants to different experimental groups

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16
Q

purposive sampling

A

a biased sampling technique in which only certain kinds of people are included in the sample

17
Q

snowball sampling

A

a variation of purposive sampling in which participants are asked to recommend acquaintances to participate in a study

18
Q

quota sampling

A

a biased sampling technique in which a researcher identifies subsets of the population of interest, sets a target number for each category in the sample, and nonrandomly selects individuals within each category until the quotas are full