Representative sampling is a type of statistical sampling in which a researcher attempts to select individuals which are representative of a larger population. In statistical sampling, people gather data from a small group and try to extrapolate the results to make generalizations about a larger group. Truly representative sampling is extremely hard to accomplish, and researchers may dedicate a great deal of time and funding to getting 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 might not be aware of it; the next time you open a newspaper, look for an article which talks about the result of a study. A line like “67% of American pet owners sleep with their pets” is the result of a representative sample of pet-owning Americans. Incidentally, that number comes from the Sealy® Mattress Company.
In order to get a representative sample, the researchers must first identify the population being sampled. In the example above, the researchers wanted to collect data on how many Americans slept with their animals, so the population was American pet owners. The next step for the researchers is finding a way to randomly select people from this population so that they can survey these individuals for data.
If the researchers collect too heavily from one segment of the population, such as all American pet owners going to veterinary clinics in the city of Chicago, the result is not a representative sample of the population being studied. Therefore, researchers must think of a multitude of methods for collecting data to ensure that evenly samples all aspects of the population being studied.
When you read a study which has been conducted with the use of representative sampling, it is a good idea to find out which methods the researchers used. Sampling error can yield incorrect results, and therefore you want to know how the data was collected, who it was collected from, and what sort of controls were in place to ensure that the sampling was representative. By using critical thinking to look at statistics and representative sampling, you will be able to determine whether or not they are truly useful and applicable.
Some clues that a study might not be valid include the use of self-response surveys, which have a high rate of non-response which would skew the sample, and indications that the sample was taken from a smaller subcommunity of a larger group. If you read a study that says “X% of Europeans eat toast for breakfast” and the text of the study says that the sample was obtained from people at train stations during the morning commute, this is not representative sampling.