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Systematic sampling

Systematic sampling is where we select every th member of the population to be in our sample.

For example, asking every 10th person who walks along a street to be in the sample.

Systematic sampling is where we select every th member of the population to be in our sample - at regular intervals.

  • It’s easy to understand.
  • Easier to implement than other sampling methods, because we don’t need to randomly select members of the population or even know anything about it - we# just need to select every th member.
  • It’s unbiased, because every member of the population has an equal chance of being selected for the sample (as long as we start at a random point in the population).
  • It may not give us a representative sample, because we might by chance select a sample that is not representative of the population (e.g. we might select a sample that is all from one area, or all from one age group, etc.).
  • It can be difficult to implement, if we can’t feasibly survey every th member of the population (e.g. they live in a large area).
  • It might be biased if there is a pattern in the population that coincides with the sampling interval (e.g. if we select every 10th person, and every 10th person happens to be from a certain area or age group, then our sample will be biased).