what is simple random sampling
- 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
how do you choose a simple random sample
- 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
what is an advantage of simple random sampling
- every member of the population has an equal chance of being selected
- so it is completely unbiased
what is a disadvantage that comes with simple random sampling
- 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
what is systematic sampling
where every nth member of the population you are investigating is selected
how do you choose a systematic sample
- 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
what are the advantages of using systematic sampling
- 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
what is the disadvantage that comes with using systematic sampling
if the interval coincides with a pattern in the population, it could be a biased sample
what is stratified sampling
- 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
how is stratified sampling set up
- divide the population into categories
- calculate the number needed for each category in the sample
- randomly select the sample in each category
what is the formula used to calculate the number needed for each category
(size of category in pop / total size of pop) x total sample size
what are the advantages of stratified sampling
- if the categories are disjointed this should give a representative sample
- it is useful when results may vary depending on the category
what does it mean if the categories are disjointed
- there is no overlap
- like gender or age groups
what is the disadvantage of stratified sampling
the extra detail needed can make it expensive
what is quota sampling
- 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
how do you choose a quota sample
- 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
what are the advantages of quota sampling
- 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
what are the disadvantages that come with quota sampling
- it can be biased by the interviewer
- selection isnt random so they might exclude some of the population
what is opportunity sampling
where the sample is chosen from a selection of the population that is most convenient for the sampler
how do you choose an opportunity sample
- choose members of the population that are easiest to sample
- like asking the first people you meet or sample whatever products you find
what is an advantage of opportunity sampling
data can be gathered very quickly and easily
what is a disadvantage of opportunity sampling
- it isnt random and can be very biased
- theres no attempt to make the same representative
what is cluster sampling
- when the population is divided into distinct groups
- and you expect these groups to give similar results to each other
how do you choose a cluster sample
- 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
