Types of Sampling

Question 1

What is random sampling?

Answer 1

A sampling method where each thing in our sampling frame has an equal chance of being chosen, in order to avoid bias

Question 2

What is simple random sampling?

Answer 2

A method where every sample of the required size has the same probability of being selected.

Question 3

How do you carry out simple random sampling?

Answer 3

In sampling frame each item has identifying number. Use random number generator, or ‘lottery sampling’ (names in a hat).

Question 4

Advantages of simple random sampling

Answer 4

Bias free.
Easy and cheap to implement.
Each number has a known equal chance of being selected.

Question 5

Disadvantages of simple random sampling

Answer 5

Not suitable when population size is large.

Sampling frame needed.

Question 6

What is systematic sampling?

Answer 6

Required elements are chosen at regular intervals in ordered list

Question 7

What are the three types of random sampling?

Answer 7

Simple random sampling, systematic sampling and stratified sampling

Question 8

How do you carry out systematic sampling?

Answer 8

i.e. Take every kth elements where:
𝑘=(𝑝𝑜𝑝 𝑠𝑖𝑧𝑒 (𝑁))/(𝑠𝑎𝑚𝑝 𝑠𝑖𝑧𝑒 (𝑛) )
starting at random item between 1 and 𝑘.

Question 9

Advantages of systematic sampling

Answer 9

Simple and quick to use.

Suitable for large samples/ populations.

Question 10

Disadvantages of systematic sampling

Answer 10

Sampling frame again needed.

Can introduce bias if sampling frame not random.

Question 11

What is stratified sampling?

Answer 11

Population divided into groups (strata) and a simple random sample carried out in each group.

Question 12

How do you carry out stratified sampling?

Answer 12

Same proportion (𝑠𝑎𝑚𝑝 𝑠𝑖𝑧𝑒 (𝑛))/(𝑝𝑜𝑝 𝑠𝑖𝑧𝑒 (𝑁) ) sampled from each strata.

Used when sample is large and population naturally divides into groups.

Question 13

Advantages of stratified sampling

Answer 13

Reflects population structure.

Guarantees proportional representation of groups within population.

Question 14

Disadvantages of stratified sampling

Answer 14

Population must be clearly classified into distinct strata.

Selection within each stratum suffers from same disadvantages as simple random sampling:
Not suitable when population size is large.
Sampling frame needed.

Question 15

What are the two types of non-random sampling?

Answer 15

Quota sampling and Opportunity sampling

Question 16

What is quota sampling?

Answer 16

A method where an interviewer or researcher selects a sample that reflects the characteristics of the whole population

Question 17

What is opportunity sampling?

Answer 17

Taking the sample from people who are available at the time the study is carried out and who fit the criteria you are looking for - aka convenience sampling

e.g. first 20 people you meet outside a supermarket on a Monday morning who are carrying shopping bags

Question 18

Advantages of quota sampling

Answer 18

• Allows small sample to still be representative of population.
• No sampling frame required.
• Quick, easy, inexpensive.
• Allows for easy comparison between different groups in population.

Question 19

Disadvantages of quota sampling

Answer 19

• 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.
• Non-responses are not recorded.

Question 20

How do you carry out quota sampling?

Answer 20

The population is divided into groups according to a given characteristic (quota)

• Interviewer meets people and organises them into a quota
• This continues until all quotas have been filled

Question 21

What happens if a person refuses to be interviewed in quota sampling?

Answer 21

You simply ignore them and move onto the next person

Question 22

Advantages of opportunity / convenience sampling

Answer 22

• Easy to carry out.

- Inexpensive.

Question 23

Disadvantages of opportunity / convenience sampling

Answer 23

• Unlikely to provide a representative sample.

- Highly dependent on individual researcher.