Non-random sampling methods

Question 1

State two types of non-random sampling

Answer 1

Quota sampling, opportunity/convenience sampling and cluster sampling

Question 2

What is quota sampling

Answer 2

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.

Question 3

What are the pros of quota sampling

Answer 3

• 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

Question 4

What are the cons of quota sampling

Answer 4

• 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.

Question 5

What is opportunity/convenience sampling

Answer 5

Sample taken from people who are available at time of study, who meet criteria.

Question 6

What are the pros of opportunity/convenience sampling

Answer 6

Easy to carry out.
Inexpensive

Question 7

What are the cons of opportunity/convenience sampling

Answer 7

Unlikely to provide a representative sample.
Highly dependent on individual researcher
doesnt represent characteristics of the whole population

Question 8

What is cluster sampling

Answer 8

Non-random stratified sampling

• Define each cluster (should be representative of population)
• Collect random samples from each cluster

Question 9

What are the pros of cluster sampling

Answer 9

No sampling frame
Inexpensive (choosing clusters instead of evaluating entire population)

Question 10

What are the cons of cluster sampling

Answer 10

Unlikely to provide a representative sample because clusters tend to have similar characteristics resulting in overrepresentation within a cluster.

Question 11

What is self-selected sampling

Answer 11

• When sampling units volunteer to take part or are given the choice to take part or decline

Question 12

cons of self-selected sampling

Answer 12

• 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

Question 13

State a quota sampling method

Answer 13

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

Question 14

Limitations of a small sample

Answer 14

unlikely to be representative of population