Sampling

Question 1

Population:

Answer 1

A group of people who are the focus of the researcher’s interest, from which a smaller sample is drawn.

Question 2

Sample:

Answer 2

A group of people who take part in a research investigation. The sample is drawn from a target population and is presumed to be representative of that population.

Question 3

Sampling techniques:

Answer 3

The method used to select people from the population.

Question 4

Bias:

Answer 4

Certain groups may be over or under-represented within the sample selected. Limits the extent to which generalisations can be made to the target population.

Question 5

Generalisation:

Answer 5

The extent to which findings and conclusions from a particular investigation can be broadly applied to the population. Depends on how representative the sample is.

Question 6

Random Sample:

Answer 6

1. All members of the target population have an equal chance of being selected.
2. A complete list of all members are obtained and assigned a number.
3. The sample is generated using a lottery method.

Question 7

Random Sample: Evaluation

Answer 7

1. Free from researcher bias, researcher has no influence over who is selected.
2. Prevents them from choosing people to support their hypothesis.
3. Time consuming and difficult, a complete list of the target population may be difficult to obtain.
4. May end up with an unrepresentative sample- the laws of probability suggest that a more representative sample.
5. Participants may refuse to take part.

Question 8

Systematic Sample

Answer 8

1. Every nth member of the target population is selected.
2. A sampling frame is produced, which is a list of people in a target population are organised into alphabetical order for example.
3. A sampling system is nominated, every 3rd person, or this interval may be determined randomly

Question 9

Systematic Sample: Evaluation

Answer 9

1. Avoid researcher bias.
2. Once the system for selection has been established the researcher has no influence over who is chosen.
3. Fairly representative.
4. Not truly unbiased unless the system of selection is randomly selected.

Question 10

Stratified Sample:

Answer 10

1. The composition of the sample reflects the proportions of people certain sub-groups (strata) within the target or wider population.
2. Researcher identifies the strata that make up the population.
3. Then the proportions needed for the sample to be representative are worked out.
4. Then the pps that make up each stratum are selected using random sampling.

Question 11

Stratified Sample: Evaluation

Answer 11

1. Avoids researcher bias.
2. Representative sample, generalisation is possible.
3. The identified strata cannot reflect all the ways that people are different, so complete representation of the target population is not possible.