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?

A

external

23
Q

random assignment increases which validity?

A

internal

24
Q

random assignment helps to eliminate _______

A

confounds

25
Q

when can nonprob/ non random sampling be used?

A

when external validity is not vital to the study

26
Q

4 techniques of non random sampling

A

convenience
purposive
snowball
quota

27
Q

in non prob sampling what does the researcher know about a participant’s chances of being selected?

A

nothing

28
Q

convenience sampling

A

selecting participants who are readily available

29
Q

purposive sampling

A

researchers judge and select who they think the best participants will be

30
Q

snowball sampling

A

participants are asked to recommend others to participate

31
Q

quota sampling

A

select specified proportions of certain kinds of participants

32
Q

does sample size affect representativeness?

A

No

33
Q

what is a typical statistically valid sample size?

A

1000-2000 cases

34
Q

what quantifies sampling error?

A

margin of error of the estimate

35
Q

an increase in sample size is shown to be related to a decrease in what?

A

margin of error