Chapter 7 Sampling Flashcards

1
Q

generalizability and its other term

A

ensuring that the sample is a good representation of the pop. of interest; representativeness

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2
Q

sampling error

A

extent to which characteristics of individuals selected for the sample differ from those of the population

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3
Q

main component of a biased sample

A

not all members of a pop. have an equal prob. of being included

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4
Q

which validity do biased samples lack?

A

external

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5
Q

main component of an unbiased sample

A

all members of the pop. of interest have an equal prob of being included

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6
Q

probability sampling vs non-prob sampling

A

prob: every member of pop of interest has an EQUAL AND KNOWN chance of being selected for the sample, random
non-prob: produces biased samples, not random

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7
Q

5 techniques of random sampling

A

SRS
systematic
cluster
stratified
oversampling

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8
Q

how is SRS characterized?

A

equality: each member of pop of interest has an equal chance of being chosen
independence: selecting 1 person doesnt affect the likelihood of selecting any other

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9
Q

disadv of SRS

A

time-consuming and can be difficult

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10
Q

systematic sampling

A

randomly generate a number N and select every Nth person/thing

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11
Q

cluster sampling

A

pop of interest is divided into clusters (usually naturally occurring groups ex: location)

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12
Q

multistage sampling

A

variation of cluster sampling: subset of a subset of clusters

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13
Q

advantages of cluster

A

easier to contact participants and dont need a sample frame for entire population

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14
Q

sampling frame

A

list of all members of a population

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15
Q

stratified random sampling

A

divides the pop into strata/subgroups that are of interest in hopes of including participants from distinct strata

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16
Q

3 steps of stratified random sampling

A
  1. divide pop into strata
  2. randomly select cases from each subgroup
  3. add up all participants from dif strata together
17
Q

sample sizes in stratified random sampling can be of 2 types:

A

equal or proportionate

18
Q

oversampling

A

variation of stratified sampling; one or more groups is overrepresented

19
Q

when is oversampling most appropriate?

A

when the distribution of subgroups isnt really equal

20
Q

random sampling

A

using a random method to create a sample so each member of the pop of interest has an equal chance of being selected

21
Q

random assignment

A

used in experiments to assign participants to groups at random

22
Q

random sampling increases which validity?

23
Q

random assignment increases which validity?

24
Q

random assignment helps to eliminate _______

25
when can nonprob/ non random sampling be used?
when external validity is not vital to the study
26
4 techniques of non random sampling
convenience purposive snowball quota
27
in non prob sampling what does the researcher know about a participant's chances of being selected?
nothing
28
convenience sampling
selecting participants who are readily available
29
purposive sampling
researchers judge and select who they think the best participants will be
30
snowball sampling
participants are asked to recommend others to participate
31
quota sampling
select specified proportions of certain kinds of participants
32
does sample size affect representativeness?
No
33
what is a typical statistically valid sample size?
1000-2000 cases
34
what quantifies sampling error?
margin of error of the estimate
35
an increase in sample size is shown to be related to a decrease in what?
margin of error