State two types of non-random sampling
Quota sampling, opportunity/convenience sampling and cluster sampling
What is quota sampling
Population divided into groups according to characteristic.
A quota of items/people in each group is set to try and reflect the group’s proportion in the whole population.
Interviewer selects the actual sampling units.
What are the pros of quota sampling
- Allows small sample to still be representative of population.
- No sampling frame required.
- administration is relatively easy
- cheap (costs kept to a minimum)
- Allows for easy comparison between different groups in population.
- never say QUICK
What are the cons of quota sampling
- Non-random sampling can introduce bias.
- Population must be divided into groups, which can be costly or inaccurate.
- Increasing scope of study increases number of groups, adding time/expense.
- judgemetn of interviewer can affect choice of smaple - bias
- Non-responses are not recorded
- not possible to estimate sampling errors due to a lack of randomness.
What is opportunity/convenience sampling
Sample taken from people who are available at time of study, who meet criteria.
What are the pros of opportunity/convenience sampling
Easy to carry out.
Inexpensive
What are the cons of opportunity/convenience sampling
Unlikely to provide a representative sample.
Highly dependent on individual researcher
doesnt represent characteristics of the whole population
What is cluster sampling
Non-random stratified sampling
- Define each cluster (should be representative of population)
- Collect random samples from each cluster
What are the pros of cluster sampling
No sampling frame
Inexpensive (choosing clusters instead of evaluating entire population)
What are the cons of cluster sampling
Unlikely to provide a representative sample because clusters tend to have similar characteristics resulting in overrepresentation within a cluster.
What is self-selected sampling
- When sampling units volunteer to take part or are given the choice to take part or decline
cons of self-selected sampling
- someone may take part but refuse to answer some questions, so it can bias results
- if many people decline participation, it can affect results
- prone to volunteer bias
State a quota sampling method
For this scenario we’d likely use quota sampling, i.e.
As with stratified sampling, divide population into groups according to characteristic of interest, then determine size of each group in sample to reflect proportions within the population.
But instead of random sampling within each group, we actively choose people within each group via suitable means (e.g. advertising), until the ‘quota’ for each group is filled. no more people are interviewed when quota is met
Limitations of a small sample
unlikely to be representative of population
