Sampling

Question 1

Usually we want to know about general/generalisable patterns/trends
Usually can’t collect data from everyone we’re interested in as it is

Answer 1

expensive
time-consuming
sometimes not actually possible

Question 2

Ask a few people and hope they give a

Answer 2

good representation of ‘everyone’

Question 3

Population:

Answer 3

group of people/organisations/whatever that we want to know about

Question 4

Population may be a quite focused group, sometimes we talk about a TARGET POPULATION, e.g.

Answer 4

certain age range, people who drive cars, etc.

Question 5

Sample is the

Answer 5

group of people/organisations/whatever from whom we collect data

Question 6

N =

Answer 6

population size

Question 7

n =

Answer 7

sample size

Question 8

Complete enumeration =

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everyone is counted

Question 9

Sample distribution is not always a good representation of population distribution as not all data has been

Answer 9

collected

Question 10

Want sample data to be

Answer 10

representative of the population we are studying

Question 11

Sample data to be representative of population: everyone in the population has to have a chance of being selected into the sample.
This is called:

Answer 11

Probability sampling or random sampling

Question 12

Sample data to be representative of population: if we systematically exclude anyone, then our sample will be

Answer 12

biased - not a good reflection of the population

Question 13

Sample data to be representative of population: sampling variation is an inherent part research process. But this strategy should give us results that are, on the whole, a good indication of

Answer 13

what’s going on in the population

Question 14

Probability sampling: every unit (case) in the population has a

Answer 14

known, non-zero probability of being selected into the sample

Question 15

[PS]Simple random sampling: every unit has the

Answer 15

same probability of selection

Question 16

[PS]Stratified sampling: selection probabilities set separately for

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different strata (selections of the population)

Question 17

[PS]Cluster sampling: sample larger groups that contain

Answer 17

a number of cases (e.g. sample whole schools and then study all children within a school)

Question 18

[PS]Multistage sampling: combine a

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number of different approaches

Question 19

Non-probability sampling: some units (cases) in the population have unknown probabilities of being selected, and/or some have

Answer 19

no chance of being selected into the sample

Question 20

[NPS] Purposive sampling: researcher uses his/her own judgement to

Answer 20

select subjects

Question 21

[NPS] Convenience sampling: researcher uses some strategy that is

Answer 21

convenient, e.g. street polling

Question 22

[NPS] Quota sampling: researcher finds a certain number (quota) of subjects with

Answer 22

key characteristics, e.g. so many males/females, so many of whatever age, occupation

Question 23

Sample size: all else equal, larger samples give

Answer 23

more precise estimates of the things we want to measure

Question 24

Sample size: smaller samples are more prone to being

Answer 24

skewed by unusual cases

Question 25

we can use different units of analysis in our research - the choice is

Answer 25

important

Question 26

we rely a great deal on gathering information from

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samples to tell us about the populations to which they belong

Question 27

different strategies for

Answer 27

sampling

Question 28

beware bias in sampling: some cases which are part of the target population being

Answer 28

systematically excluded from the sample

Question 29

All else equal, larger samples give us more

Answer 29

precise information