One of the most important issues about any type of method is how representative of the population the results are.
The population is the group of people from whom the sample is drawn. For example if the sample of participants is taken from sixth form colleges in Hull, the findings of the study can only be applied to that group of people and not all sixth form students in the UK and certainly not all people in the world.
Obviously it is not usually possible to test everyone in the target population so therefore psychologists use sampling techniques to choose people who are representative (typical) of the population as a whole.
Opportunity sampling is the sampling technique most used by psychology students. It consists of taking the sample from people who are available at the time the study is carried out and fit the criteria your are looking for.
This may simple consist of choosing the first 20 students in your college canteen to fill in your questionnaire.
It is a popular sampling technique as it is easy in terms of time and therefore money. For example the researcher may use friends, family or colleagues. It can also be seen as adequate when investigating processes which are thought to work in similar ways for most individuals such as memory processes. Sometimes, particularly with natural experiments opportunity sampling has to be used as the researcher has no control over who is studied.
However, there are many weaknesses of opportunity sampling. Opportunity sampling can produce a biased sample as it is easy for the researcher to choose people from their own social and cultural group. This sample would therefore not be representative of your target population as you friends may have different qualities to people in general.
A further problem with opportunity sampling is that participants may decline to take part and your sampling technique may turn into a self selected sample.
This is a sampling technique which is defined as a sample in which every member of the population has an equal chance of being chosen. This involves identifying everyone in the target population and then selecting the number of participants you need in a way that gives everyone in the population an equal chance of being picked. For example, you could put all of the names of the students at your college in a hat and pick out however many you need.
Random sampling is the best technique for providing an unbiased representative sample of a target population.
However random sampling does have limitations. Random sampling can be very time consuming and is often impossible to carry out, particularly when you have a large target population, of say all students. For example if you do not have the names of all the people in your target population you would struggle to conduct a random sample. If you ask people to volunteer for a study the sample is already not random as some people may be more or less likely to volunteer for things. Similarly if you decided to put out an advert for participants it would be almost impossible to guarantee that every member of your target population has an equal chance of viewing the advert.
Stratified sampling involves classifying the population into categories and then choosing a sample which consists of participants from each category in the same proportions as they are in the population. For example, if you wanted to carry out a stratified sample of students from a sixth form college you might decide that important variables are sex, 1st or 2nd years, age, have a part-time job and so on. You could then identify how many participants there are in each of these categories and choose the same proportion of participants in these categories for your study.
The strength of stratified sampling is therefore that your sample should be representative of the population. However, stratified sampling can be very time consuming as the categories have to be identified and calculated. As with random sampling, if you do not have details of all the people in your target population you would struggle to conduct a stratified sample.
If the sample is not randomly selected from the categories it is then called a quota sample.
Snowball sampling can be used if your population is not easy to contact. For example if you were interested in studying students who take illegal drugs you may ask a participant who fits your target population to tell their friends about the study and ask them to get in touch with the researcher and so on.
Self selected sampling
Self selected sampling (or volunteer sampling) consists of participants becoming part of a study because they volunteer when asked or in response to an advert. This sampling technique is used in a number of the core studies, for example Milgram (1963).
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. However, the type of participants who volunteer may not be representative of the target population for a number of reasons. For example, they be more obedient, more motivated to take part in studies and so on.