Sampling Flashcards
Target Population
Target population refers to the entire group of individuals a researcher is interested in studying and from which a sample is drawn. It represents the wider population to which the study’s findings can be generalised.
Sample
A sample is a smaller group selected from a target population that is used in a study to represent the wider population.
If the results obtained from a study are to be generalised (applied to the rest of the population), it is important that the sample is representative. Psychologists obtain representative samples by using various methods.
Sampling Methods
A sampling method is the process by which the psychologist selects representative individuals from the sampling frame.
Sample Frame
A sampling frame is a list of all those included in the target population from which the sample will eventually be selected. For example, the names of all school children in a school taken from the registers.
Sample Size
Sample size refers to the number of participants included in a study.
The size of the sample will depend on the time and money available, however, if the sample is too small, the findings may not be representative of the whole target population.
Why is Sampling important?
The sample must be representative of the target population so that the findings can be considered generalisable. If the sample is not representative of the whole target population, the sample is said to be biased. Sampling is also a consideration when judging the population validity of research.
What are the 3 types of sampling?
- Random sampling
- Opportunity sampling
- Volunteer sampling
Random methods
Random sampling methods ensure that every individual in the target population has an equal chance of being selected.
Features of random methods
- Contains a sampling frame
- Large sample
Name some random methods of sampling
- Simple random sampling
- Stratified random sampling
- Systematic random sampling
Simple random sampling
Each individual in the target population has an equal chance of selection, and names are selected from the sampling frame at random.
Stratified random sampling
The sampling frame is divided into strata (sub-groups) and a random sample is chosen from each stratum.
Systematic sampling
A series of names is taken at regular intervals from the sampling frame.
Non-random methods
Non-random sampling methods do not give every individual in the target population an equal chance of being selected, which can introduce bias.
Features of non-random methods
- No sampling frame
- Smaller sample
Name some non-random methods of sampling
- Quota sampling (opportunity)
- Snowball sampling (volunteer)
Quota sampling (opportunity)
People of different types are chosen by interviewers to ensure a certain number of each type in the sample.
Snowball sampling (volunteer)
Start with one member of the population and that person will divulge the names of others who might cooperate.
