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Maths 11 - Sampling, Data Representation And Interpretation > Sampling Methods > Flashcards

Sampling Methods Flashcards

1
Q

what is simple random sampling

A
  • where every person or item in a population has an equal chance of being in the sample
  • and each selection is independent of the others
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2
Q

how do you choose a simple random sample

A
  • give a number to each population member from a full list of the population
  • generate a list of random numbers
  • match them to the numbered members to select the sample
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3
Q

what is an advantage of simple random sampling

A
  • every member of the population has an equal chance of being selected
  • so it is completely unbiased
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4
Q

what is a disadvantage that comes with simple random sampling

A
  • it is inconvenient if the population is spread over a large area
  • it might be difficult to track down the selected members
  • like in a nationwide sample
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5
Q

what is systematic sampling

A

where every nth member of the population you are investigating is selected

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6
Q

how do you choose a systematic sample

A
  • number each member of the population from a full list
  • calculate a regular interval to use by dividing the population size by the sample size
  • generate a random starting point to choose the first member of the sample
  • keep adding the interval to the starting point to select your sample
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7
Q

what are the advantages of using systematic sampling

A
  • it can be used for quality control in a production line
  • a machine can be set up to sample every nth term
  • it should give an unbiased sample
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8
Q

what is the disadvantage that comes with using systematic sampling

A

if the interval coincides with a pattern in the population, it could be a biased sample

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9
Q

what is stratified sampling

A
  • when a population is divided into categories like gender

- and you use the same proportion of each category in the sample as there is in the population

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10
Q

how is stratified sampling set up

A
  • divide the population into categories
  • calculate the number needed for each category in the sample
  • randomly select the sample in each category
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11
Q

what is the formula used to calculate the number needed for each category

A

(size of category in pop / total size of pop) x total sample size

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12
Q

what are the advantages of stratified sampling

A
  • if the categories are disjointed this should give a representative sample
  • it is useful when results may vary depending on the category
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13
Q

what does it mean if the categories are disjointed

A
  • there is no overlap

- like gender or age groups

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14
Q

what is the disadvantage of stratified sampling

A

the extra detail needed can make it expensive

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15
Q

what is quota sampling

A
  • when an interviewer for example is given a quota of people in each category to interview
  • then they choose people to interview until the quotas are fulfilled
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16
Q

how do you choose a quota sample

A
  • divide the pop into categories
  • give each category a quota (number of members to sample)
  • collect data until all quotas are met in all categories
17
Q

what are the advantages of quota sampling

A
  • it is easy for the interviewer
  • as they dont need to access the whole population or a list of every member
  • the interviewer continues to sample until all the quotas are met
  • so non-response is less of a problem
18
Q

what are the disadvantages that come with quota sampling

A
  • it can be biased by the interviewer

- selection isnt random so they might exclude some of the population

19
Q

what is opportunity sampling

A

where the sample is chosen from a selection of the population that is most convenient for the sampler

20
Q

how do you choose an opportunity sample

A
  • choose members of the population that are easiest to sample
  • like asking the first people you meet or sample whatever products you find
21
Q

what is an advantage of opportunity sampling

A

data can be gathered very quickly and easily

22
Q

what is a disadvantage of opportunity sampling

A
  • it isnt random and can be very biased

- theres no attempt to make the same representative

23
Q

what is cluster sampling

A
  • when the population is divided into distinct groups

- and you expect these groups to give similar results to each other

24
Q

how do you choose a cluster sample

A
  • divide the population into clusters covering the whole population
  • where no member of the population belongs to multiple clusters
  • randomly select clusters to use in the sample base on required sample size
25
Q

what are the two ways cluster sampling can be executed as the sample is being picked

A
  • either use all the members of the selected clusters (a one stage cluster sample)
  • or randomly sample within each cluster to form a sample (a two stage cluster sample)
26
Q

what are the advantages of cluster sampling

A
  • it can be more practical in certain situations (quicker / cheaper)
  • you can incorporate other sampling methods, making it adaptable
27
Q

what disadvantages come with cluster sampling

A
  • because you only sample certain clusters, the results could be less representative
  • its not always possible to separate a population into clusters in a natural way
28
Q

what is self selection sampling

A
  • where the people choose to be part of the sample

- like choosing to be in a questionnaire or volunteering

29
Q

how do you create a self-selection sample

A
  • advertise / appeal to the whole population for participation in the sample
  • either use everyone who responds as the sample
  • or take a sample of them to represent the population
30
Q

what is an example of how the population could be appealed to

A

by offering payment

31
Q

what are the advantages of self selection sampling

A
  • it requires little time or effort in finding sample members as they contact you
  • people who volunteered are more likely to respond
  • it could be the only way to get people to take part in a study
  • or to find members of a population
32
Q

what is the disadvantage of self selection sampling

A
  • there can easily be trends within the respondents
  • such as people having strong opinions
  • which could lead to bias

Maths 11 - Sampling, Data Representation And Interpretation (2 decks)

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