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Sampling Techniques: Systematic Sampling





Systematic Sampling As with simple random sampling, the technique of systematic sampling is used to obtain a sample from the defined population. This technique can be used if all members in the defined population have already been placed on a list in random order. Suppose the researcher wants to select a sample of 100 pupils from a census list of 1000 pupils. To use systematic sampling, the researcher first divides the population by the number needed for the sample (1000 - 100 = 10). Then the researcher selects at random a number smaller than the number arrived at by the division (in this example, a number smaller than 10). Then, starting with that number (e.g., 8), she selects every tenth name from a list of the population. Systematic sampling is a slightly easier procedure to use than simple random sampling. It differs from simple random sampling in that each member of the population is not chosen independently. Once the first member has been selected, all the other members of the random sample are automatically determined. Systematic sampling can be used instead of simple random sampling if one is certain that the population list is in random order. If there is any possibility of periodicity in the list (that is, if every nth person on the list shares a characteristic that is not shared by the entire population), then simple random sampling should be used instead.