Sampling of participants

Psychology AS · Research methodology. The idea in plain words, the rules to remember, the mistake to avoid and a worked example, written and checked by Mega Lecture.

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The idea

The population is the whole group the researcher wants to find out about. It is usually too large to test, so a smaller group, the sample, takes part. The aim is a sample that is typical of the population, so that the results can be generalised to it.

There are three techniques to know. In opportunity sampling the researcher uses people who are available at the time. In random sampling every member of the population has an equal chance of being chosen. In volunteer (self-selecting) sampling people put themselves forward, for example by replying to an advertisement.

Each technique has strengths and weaknesses to do with speed, bias and how representative the sample is.

Rules to remember

Population: all the people the study is about. Sample: the people who actually take part.
Opportunity sampling: uses whoever is available. Quick and easy, but likely to be biased and unrepresentative.
Random sampling: equal chance for everyone, e.g. names from a hat or a random number generator.
Random sampling avoids researcher bias but needs a full list of the population and takes time; those chosen may refuse.
Volunteer (self-selecting) sampling: people respond to an advert or request.
Volunteers are willing and can come from a wide area, but they may be a certain type of person, so the sample can be biased.
Generalisation: applying the results from the sample to the population; it needs a representative sample.

Common mistake

Students call any quick sample "random". It is random only if every member of the population had an equal chance of being picked; stopping people in a corridor is opportunity sampling.

Worked example

A researcher studying sleep in university students emails every student at one university and tests the first 30 who reply. Name the technique and one weakness.

The students choose to reply, so they select themselves.
This is volunteer (self-selecting) sampling, not random, because the researcher did not pick names by chance.
People who reply may be more interested in sleep or more helpful than most students.

Answer: Volunteer sampling; the sample may be biased, so the results are harder to generalise to all students.

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