3. Population, Sample and Sampling

Population: The entire group of research interest from which a sample is drawn & to which the researcher will seek to generalise the results of the investigation

→ typically has one or more characteristics in common

Sample: A subset or part of the population that is selected for research purposes.

→ researchers attempt to generalise the results obtained from the sample as to the population from which it is drawn.

→ important that the sample accurately reflects the entire population of interest.

Sampling: The process by which a subset or part of the population is selected for investigation

→ Representative sample: sample that closely resembles the population which it is drawn in key characteristics

→ Biased sample: sample that does not adequately resemble the key characteristics of the population it is drawn from.

Law of large numbers: Suggests that as sample size increases, the characteristics of the sample more closely reflects with teh attributes f the population from which the sample was drawn.

Sampling techniques: (ensure quality and usefulness)

Random sampling:
Ensures every member of the population of research interest has an equal chance of being selected to be part of the sample.

$ Sample gained this way will more likely be representative of the population of interest, and participant variables will be distributed in sample in the same proportion as in population.
Adv→ Ensures highly representative sample

Lim→ Difficult, time consuming, impossible or unethical to obtain names of all members of population.

Stratified sampling

Selecting a sample from a population comprised of various subgroup, in such a way that each subgroup is represented.
Strata: subgroups

Stratum: Sample from subgroup

Sampled by the same proportions as they occur in the population of interest

Adv→

  • Enable researcher to sample specific groups within population for comparison purposes.

  • important subgroups of population are ensured fair representation

  • large enough stratified sample is probably representative of population, improving external validity.

eg/ diff organisations, race

Dis→

  • Can only be carried out if complete list of target populations are available

  • time-consuming and complex procedure

Stratified random sampling:

Identifying all people within each stratum of research interest and randomly selecting samples of a set size within each stratum

Adv→ random sampling from appropriately sized proportions of strata ensure high degree of representatives.

Lim→ time consuming, complex and difficult to achieve.

Convenience sampling: (non probability sampling)

Selecting participants who are readily or easily available

Adv→ quick and easy way of selecting participants

Lim→ produce biased sample