What is Systematic Sampling?

Anyone who has participated in team sports has likely experienced systematic sampling.

Systematic sampling is a way of conducting research that determines how to select members of a population to be studied. Many research efforts focus on getting a random sample, where every member of the population under study has an equal chance of being chosen. Another option is to take a simple random sample, where each group of predetermined size has an equal chance of being selected. An alternative is systematic sampling, where researchers select an initial member of the group and then use that as a means of selecting all other samples.

Anyone who has ever participated in team sports in a physical education class has likely had systematic sampling. A coach moves down the line of students, counting all the other students, and divides the line into two teams. Essentially, the coach starts with a starting student and takes all the other students with him, creating a sample of the original group that will become either team one or team two.

Normally, it would be impractical to choose “everyone else” from a large group. Instead, the researchers determine ok – th element. K is defined as the number of population elements that will be skipped between choices and must remain constant throughout the sample selection process. If someone takes a sample decides that the sample starts with one and every 50th element thereafter will be taken as part of the sample, k is 50. The sampler will pull or test 1.51, 101, 151 and so on, until it reaches the end of the group.

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In statistics, a simple random sample is often preferred because there are many operations that require one, so that more information about something can be evaluated. Systematic sampling is highly useful and suitable for the purpose of determining information about a population for reasons such as quality control. It is important to note that the sample is not entirely random, although it may be one of the best approximations to randomness.

Much of the accuracy of a systematic sample depends on choosing a sample size that is representative of the population. This means that k must be small enough to create an adequate sample size that informs researchers or testers about what is happening in the general population. K cannot be too small or the group it selects is too large and may be impractical and expensive to test. It should be noted that a systematic sample can be from people, animals or things, depending on what is being tested.

Systematic sampling appears frequently in manufacturing. Many factories automatically inspect or de-line every k-th product. Some food manufacturers in particular use this as a selling point to demonstrate high standards of quality control.

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