WHAT IS SAMPLING?
You can't test everyone.
To get around this limitation on their research, psychologists will identify the target population (everyone they'd like to test) then recruit a sample that they think is representative of that population.
If the sample really is representative, the results of the sample could be generalised to the target population.
If the sample isn't representative, then the results will not be generalisable and will only tell you about the sample itself.
Target populations have to be realistic. "Everyone in the world" is NOT a realistic target population. A target population is usually "everyone in my Sixth Form" or "everyone in my workplace". Professional researchers might be able to sample "everyone in the country" but this is uncommon.
PSYCHOLOGY'S FRUIT FLIES
Ariel Rubenstein (1982) points out that too much cognitive research is carried out on college students. He compares them to fruit flies, which are used in genetic research because they are small and convenient and have very short life spans (so you can quickly see the effect of a genetic change on a fly's descendants); in contrast, there's not much genetic research into elephants.
Rubenstein points out that much cognitive psychology boils down to the "science of the behavior of the college sophomore" - someone who is white, middle-class, educated and 18- to 20- years old.
The sample is those members of the target population who happen to be available at the time.
Opportunity sampling involves getting hold of the nearest and most convenient people: your friends, neighbours and passers-by. It’s easy to use, but there’s a big risk of experimenter bias, because only people near to you or known to you have any chance of being in the study.
"Random" is often used as a slang word to mean "unplanned" or "without thought". An opportunity sample is what you probably think of as a "random sample" because it doesn't take much preparation and you might select people on impulse.
The sample is those members of the target population who select themselves.
Volunteer sampling involves asking for volunteers – for example, advertising your study on a notice board or on Facebook and using anyone who signs up.
Because they have volunteered, this sort of sample might be more committed than a sample that has to be approached and asked. That might be important if the research involves tasks that are stressful or boring.
This produces a much more varied sample than opportunity sampling because there's no experimenter bias. However, the sample may still be unrepresentative because you only get certain sorts of people volunteering (the ones interested in Psychology, people with a lot of free time). You could think of this as participant bias instead of experimenter bias. What's more, people have to see and understand the advert to have a chance of being in the sample, so that might rule out participants who speak other languages, don't read newspapers or who aren't online.
It also takes longer (because you have to wait for the volunteers to show up).
Psychologists aren't consistent in the terms they use. Edexcel call this technique volunteer sampling but you will see other books and websites calling it "self-selecting sampling".
The sample is members of the target population selected without any bias.
This sounds like an ideal method, because you use an unbiased way of identifying people in the target population, for example by pulling their names out of a hat. However, it’s often very difficult to get a complete list of everyone in the target population, so this sampling technique is normally only used when the target population is very small; for example randomly selecting people from out of your class.
Also, just because the sample was selected in an unbiased way, it doesn't mean it must be representative. You could selected people randomly and still find you had an unrepresentative sample that was all-boys.
"Random" is often used as a slang word to mean "unplanned" or "without thought". A truly random sample isn't like that at all. It takes a lot of planning and thought. BEWARE. If you're tempted to say that a sampling technique is "random" because you're just picking anyone you see nearby without thinking about it, you really mean "opportunity sampling".
The sample is members of the target population selected in an unbiased way but guaranteed to be representative in certain ways.
Strata are sub-groups within the target population (like boys and girls or different age groups). This technique involves working out the strata you need in your sample and how many people there should be in each, then filling the strata through random sampling.
This is much more representative than normal random sampling because you make sure that each sub-group gets represented. It’s probably the most representative and unbiased technique there is, but it’s very fiddly and only works if you have a complete list of everyone in the target population. An example of a stratified sample might be a school that makes sure there is a random group of 1st year students, a random group of 2nd year students, etc, making up a stratified sample of the entire student population.
Researchers have to decide on important strata in advance and this can cause problems. It's not always obvious which strata are important (do you need to stratify tour sample by gender? by race? by IQ? by personality?). Some strata might be difficult to operationalise; for example, you might want to stratify your sample into people 's sexual orientation, to match the proportion of straight and gay people in the target popuation, but it may be hard to find this sort of information out.
EVALUATING SAMPLING TECHNIQUES
The strengths and weaknesses of these four techniques are summarised below:
There are reasons why researchers might choose some sampling techniques rather than others:
Cluster sampling isn't mentioned in the Edexcel Unit 1 Specification, but I'm adding it here because you may end up using it in your own practical investigations.
Cluster sampling selects members of the target population who have already been gathered together for another purpose.
Clusters are groups of peope in pre-existing groups that belong to the target population. It might include classes or clubs within a school population, churches within a religious population or families within a neighbourhood population.
The main advantage with a cluster sample is convenience: you can just go to the lesson or club meeting and test everyone there.
Another advantage may be the lack of experimenter bias. Unlike an opportunity sample, the experimenter doesn't choose these people because of personal characteristics (eg friends) but just because they are members of the cluster. (Of course, if the experimenter is also a member of the cluster, that destroys this advantage.)
A final advantage is that a cluster population can be used if it's impossible to discover all the details of the target population. For example, if your target population is "skateboarders", you might have difficulty getting a full list of all those people or reaching out to them for an opportunity or volunteer sample. But you could make a cluster sample out of the skateboarders who use your local park.
The main disadvantage is unrepresentativeness. The cluster may be unrepresentative of the target population. Crucially, if you don't know the characteristics of the target population, it's difficult to tell how representative or unrepresentative it is.
APPLYING SAMPLING TECHNIQUES IN PSYCHOLOGY