Representative sampling is a statistical method used to select individuals who are representative of a larger population. It allows researchers to study a population without studying every individual. Researchers must identify the population to be sampled and randomly select people to ensure even sampling. Sampling error can produce erroneous results, so it’s important to know how data was collected and what controls were in place. Self-response surveys and samples taken from smaller subcommunities can skew results.
Representative sampling is a type of statistical sampling in which a researcher attempts to select individuals who are representative of a larger population. In statistical sampling, people collect data from a small group and try to extrapolate the results to make generalizations about a larger group. Truly representative sampling is extremely difficult to achieve, and researchers can spend significant time and funding to obtain the most representative sample possible.
As a research tool, statistical sampling is extremely valuable. It allows people to study a population without studying every single individual in that population. Average individuals are quite familiar with statistical sampling, even though they may not be aware of it; Next time you open a journal, look for an article about a study result. A line like “67% of American pet owners sleep with their pets” is the result of a representative sample of American pet owners. Incidentally, that number comes from the Sealy® Mattress Company.
To obtain a representative sample, researchers must first identify the population to be sampled. In the example above, the researchers wanted to collect data on how many Americans slept with their pets, so the population was American pet owners. The next step for the researchers is to find a way to randomly select people from this population so they can poll these individuals for data.
If researchers collect too heavily from one segment of the population, such as all American pet owners who go to veterinary clinics in the city of Chicago, the result is not a representative sample of the population studied. Therefore, researchers have to think of a multitude of methods for collecting data to ensure that they evenly sample all aspects of the population being studied.
When you read about a study that was conducted using representative sampling, it’s a good idea to find out what methods the researchers used. Sampling error can produce erroneous results and so you want to know how the data was collected, by whom it was collected, and what sort of controls were in place to ensure that sampling was representative. By using critical thinking to look at the statistics and representative sampling, you will be able to determine if they are truly useful and applicable.
Some clues that a study may be invalid include the use of self-response surveys, which have a high non-response rate which would skew the sample, and indications that the sample was taken from a smaller subcommunity of a larger group. ample. If you read a study that says “X% of Europeans eat toast for breakfast” and the text of the study says the sample was obtained from people in train stations on their commute, this is not representative sampling.
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