What Systematic random sample is
A systematic random sample is a type of probability sample in which a population is selected by using a randomly determined starting point, and then selecting every nth member of the population after that. This technique is used when a population is too large to select from in a practical manner.
Steps for Systematic Random Sample:
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List the population: Make an organized list of each member in the population.
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Determine the sample size: Decide how many members of the population will be included in the sample.
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Calculate the sampling interval: Divide the population size by the sample size to determine the sampling interval.
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Select the starting point: Use a random number generator to select a number between 1 and the sampling interval. This will be the starting point for the sample.
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Select the sample: Starting at the randomly determined starting point, select every nth member in the population until the desired sample size is reached.
Examples
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A researcher wishes to survey a college campus to determine student attitudes toward free speech on campus. She uses a systematic random sample to select 500 students out of a population of 10,000.
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A marketing firm wishes to get an accurate estimate of consumer preferences for a new product they are launching. They use a systematic random sample to survey 1,000 people out of a population of 10,000,000.
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A polling company wants to get an accurate estimate of public opinion on a certain political issue. They use a systematic random sample to survey 3,000 people out of a population of 100,000,000.