Sampling Methods | Types and Techniques ExplainedBy Saul McLeod, Ph.D. Show
Definitions
The Purpose of SamplingIn 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. This is important because we want to generalize from the sample to target population. The more representative the sample, the more confident the researcher can be that the results can be generalized 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. Many psychology studies have a biased sample because they have used an opportunity sample that comprises university students as their participants (e.g. Asch). OK, so you’ve thought up this brilliant psychological study 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. The one chosen will depend on a number of factors (such as time, money etc.). Random SamplingRandom sampling is a type of probability sampling where everyone in the entire target population has an equal chance of being selected. 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.
Stratified SamplingDuring stratified sampling, 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, gender 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).
Opportunity SamplingUses 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.
Systematic SamplingChooses subjects in a systematic (i.e. orderly / logical) 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.
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 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! How to reference this article:How to reference this article:McLeod, S. A. (2019, August 03). Sampling methods. Simply Psychology. www.simplypsychology.org/sampling.html How to reference this article:How to reference this article:McLeod, S. A. (2019, August 03). Sampling methods. Simply Psychology. www.simplypsychology.org/sampling.html Home | About Us | Privacy Policy | Advertise | Contact Us Simply Psychology's content is for informational and educational purposes only. Our website is not intended to be a substitute for professional medical advice, diagnosis, or treatment. © Simply Scholar Ltd - All rights reserved What is a sample group called?In statistics, a sample group can be defined as a subset of a population. The population, or target population, is the total population about which information is required.
What is it called when you choose your sample?Sampling is the process of selecting a representative group from the population under study. The target population is the total group of individuals from which the sample might be drawn.
What term is used to describe the subset of a selected population?A sample, in other words, is a portion, part, or fraction of the whole group, and acts as a subset of the population.
What is it called when you survey a group from the population?A census is a survey which measures an entire population. Example: The United States conducts a census of the American population every ten years. • A census is very tedious and takes a long time to. complete. Therefore, we use samples of a population to make inferences about that population.
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