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Convenience Sampling

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30 Terms

1

Convenience Sampling

choosing individuals from the population who are easy to reach results in a convenience sample

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2

why are convenience samples bad

often underrepresents the data

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3

voluntary response sampling

a sampling method that consists of people who choose to be in the sample by responding to a general invitation

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4

why are voluntary response samples bad

people who feel strongly about an issue, particularly people with strong negative feelings, are more likely to take the trouble to respond

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5

random sampling

a sampling method that involves using a chance process to determine which members of a population are included in the sample

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6

random sampling methods

simple random samples (SRS) stratified random samples cluster random samples systematic random samples

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7

bias

would consistently underestimate or consistently overestimate the value you want to know when the study is repeated many times

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8

simple random samples (SRS)

a sample chosen in such a way that every group of n individuals in the population has an equal chance of being selected as the sample

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9

sampling variability

when different samples of the same size from the population produce different estimates

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10

stratified samples

the population is divided into smaller groups, subpopulations (strata), then another random sampling method is used to create the sample

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11

cluster samples

population is divided into smaller groups, clusters, that are then randomly selected for the sample

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12

systematic samples

researchers select members of the population at the same intervals (k) determined in advance

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13

undercoverage

some members of the population are less likely to be chosen or cannot be chosen for the sample

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14

nonresponse

when an individual chosen for a sample cant be contacted or refuses to participate

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15

response bias

there is a consistent pattern of inaccurate responses to a survey question

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16

population

entire group of individuals we want info about

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17

census

collects data from every individual in the population

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18

sample

subset of individuals in the population from which we collect data

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19

confounding

occurs when two variables are associated in such a way that their effects on a response variable cannot be distinguished from each other

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20

response variable

measures the outcome of the study

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21

explanatory variable

may help predict or explain changes in a response variable

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