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In psychology, the population is also called the target population. The population is the group of people in which a researcher is interested.
The size of the population can vary widely. Some studies target the entire human population, while others are interested only in a smaller group, for example, people from specific age groups or certain professions, and so on.
Usually, researchers can't recruit the entire population to participate in their studies. Therefore, researchers instead select a small group within the population called the sample. This method in psychology is called sampling.
The sample drawn should represent the population in which the researchers are interested to make generalisations about the population. Ideally, researchers would like to select a sample with the greatest representativeness and minimal bias. Researchers can then generalise the results to the target population with greater confidence.
The following section is about the different sampling methods you need to know in A-level psychology. This section is about explaining, implementing, and evaluating each sampling technique.
An opportunity sample is a sample in which individuals are selected who are most available.
We can obtain an opportunity sample by asking members of the population if they are interested and willing to participate in the study.
A voluntary sample is a sample recruited by self-selection. In other words, participants self-select and contact the researcher.
We obtain voluntary samples through word of mouth or advertising.
A random sample is one in which everyone in the target population has an equal chance of being selected.
One possible method for selecting a random sample is the lottery method. Researchers assign a number to each potential participant and then create a list of random numbers to select participants for the random sample.
A systematic sample refers to selecting participants according to a set of patterns (also known as a sampling frame).
To draw a systematic sample, it is possible to list all the population members and then determine the desired sample size. If you divide the number of people in the target population by the desired sample size, you will get a number we call n. If you select every nth name, you will get a systematic sample of the size you want. For example, if you're going to draw a sample of 100 students from a university with 1,000 students, n = 1000/100 = 10, you can take every tenth name.
A stratified sample is one in which researchers select participants according to their frequency in the target population. The researcher identifies the different groups that make up the target population and calculates the proportions needed to make the sample representative.
The identified groups are called strata (or subgroups), such as gender or age groups. Participants are randomly selected from each stratum in proportion to their occurrence in the population. Therefore, the sample should reflect the relative percentages of subgroups in the population.
Opportunity, voluntary, random, systematic, and stratified sample.
Since researchers can't recruit the entire population to participate in a study, they
select a small group within the population called the sample. This process is called sampling.
A systematic sample is an example of sampling that refers to selecting participants according to a set of patterns (also known as a sampling frame).
To draw a systematic sample, it is possible to list all the population members and then determine the desired sample size. If you divide the number of people in the target population by the desired sample size, you will get a number we call n. If you select every nth name, you will get a systematic sample of the size you want. For example, if you're going to draw a sample of 100 students from a university with 1,000 students, n = 1000/100 = 10, you can take every tenth name.
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