In psychological research we are interested in learning about large groups of people who all have something in common. We call the group that we are interested in studying our 'target population'. In some types of research the target population might be as broad as all humans, but in other types of research the target population might be a smaller group such as teenagers, pre-school children or people who misuse drugs. It is more or less impossible to study every single person in a target population so psychologists select a sample or sub-group of the population that is likely to be representative of the target population we are interested in. If the sample we select is going to represent the target population then we need to make sure that the people in it are similar to the other members of the target population. This is important because we want to generalise from the sample to target population.
The participants in research, the sample, should be as representative as possible of the target population. The more representative the sample, the more confident the researcher can be that the results can be generalised to the target population.
One of the problems that can occur when selecting a sample from a target population is sampling bias. Sampling bias refers to situations where the sample does not reflect the characteristics of the target population.
Sampling bias can occur if the sample contains an over representation of a section of the target population. This might occur from a target population of teachers, when the sample consists of twenty teachers – sixteen males and four females. Females would appear to be underrepresented in the sample. This would mean that your sample was biased and not representative of the target population. Consequently the generalisability of any findings based on this sample would be threatened. Many psychology studies have a biased sample because they have used an opportunity sample and comprise university students as their participants (e.g. Asch, 1951).
OK, so you’ve thought up this brilliant psychological experiment and designed it perfectly. But who are you going to try it out on and how will you select your participants? There are various sampling methods (described below). The one chosen will depend on a number of factors (such as time, money etc.).
The researcher identifies the different types of people that make up the target population and works out the proportions needed for the sample to be representative.
A list is made of each variable (e.g. IQ, sex etc.) which might have an effect on the research. For example, if we are interested in the money spent on books by undergraduates, then the main subject studied may be an important variable. For example, students studying English Literature may spend more money on books than engineering students so if we use a very large percentage of English students or engineering students then our results will not be accurate. We have to work out the relative percentage of each group at a university e.g. Engineering 10%, Social Sciences 15%, English 20%, Sciences 25%, Languages 10%, Law 5%, Medicine 15% The sample must then contain all these groups in the same proportion as in the target population (university students).
Gathering such a sample would be extremely time consuming and difficult to do (disadvantage). This method is rarely used in Psychology. However, the advantage is that the sample should be highly representative of the target population and therefore we can generalise from the results obtained.
Chooses participants in a systematic (i.e. orderly) way from the target population, like every nth participant on a list of names.
To take a systematic sample, you list all the members of the population, and then decided upon a sample you would like. By dividing the number of people in the population by the number of people you want in your sample, you get a number we will call n. If you take every nth name, you will get a systematic sample of the correct size. If, for example, you wanted to sample 150 children from a school of 1,500, you would take every 10th name.
The advantage to this method is that is should provide a representative sample, but the disadvantage is that it is very difficult to achieve (i.e. time, effort and money).
This is similar to the national lottery. If the “population” is everyone who has bought a lottery ticket, then each person has an equal chance of winning the lottery (assuming they all have one ticket each). Random samples require a way of naming or numbering the target population and then using some type of raffle method to choose those to make up the sample. Random samples are the best method of selecting your sample from the population of interest. It is also the most difficult to achieve.
The advantages are that your sample should represent the target population and eliminate sampling bias, but the disadvantage is that it is very difficult to achieve (i.e. time, effort and money).
Uses people from target population available at the time and willing to take part. It is based on convenience.
An opportunity sample is obtained by asking members of the population of interest if they would take part in your research. An example would be selecting a sample of students from those coming out of the library.
This is a quick way and easy of choosing participants (advantage), but may not provide a representative sample, and could be biased (disadvantage).
This is another way of saying self selected sample. This sampling technique consists of participants becoming part of a study because they volunteer when asked or in response to an advert.
This technique, like opportunity sampling, is useful as it is quick and relatively easy to do.
It can also reach a wide variety of participants (advantage).
However, the type of participants who volunteer may not be representative of the target population for a number of reasons. For example, they may be more obedient, more motivated to take part in studies and so on (disadvantage).
Note: Participants for Milgram’s Obedience experiment were selected using volunteer sampling.
How many participants should be used? This depends on several factors; the size of the target population is important. If the target population is very large (e.g. all 4-6 yr olds in Britain) then you need a fairly large sample in order to be representative. If the target population is much smaller, then the sample size can be smaller but still be representative. There must be enough participants to make the sample representative of the target population. Lastly, the sample must not be so large that the study takes too long or is too expensive!