Systematic sampling is often used instead of random sampling. It is also called an Nth name selection technique. After the required sample size has been calculated, every Nth record is selected from a list of population members. As long as the list does not contain any hidden order, this sampling method is as good as the random sampling method. Its only advantage over the random sampling technique is simplicity. Systematic sampling is frequently used to select a specified number of records from a computer file.


Using this procedure each element in the population has a known and equal probability of selection. This makes systematic sampling functionally similar to simple random sampling. However it is not the same as SRS because not every possible sample of a certain size has an equal chance of being chosen (e.g. samples with at least two elements adjacent to each other will never be chosen by systematic sampling). It is however, much more efficient (if variance within systematic sample is more than variance of population).


1. Label each member of the sample group with a unique identification number (ID).

2. Calculate the sampling fraction by dividing the sample size to the total number of the population:

The sampling fraction result is guidance for applying systematic sampling. For example, if your sampling fraction is equal to 1/5, you will need to choose one in every five cases; that is every fifth case from the sampling frame. In instances where calculations result in a more complicated fraction, especially for large sample sizes, you can round your population to the nearest 10 or 100.

3. The first sample has to be chosen in a random manner. It is important to select the first sample randomly to ensure probability sampling aspect of the systematic sampling. In other words, if the first sample is selected from the start of the sample frame all the time, the samples between the sample fractions (samples between every fifth cases in example above) will not have a chance of being included in the sample group. Therefore, the fist case needs to be selected randomly to overcome this issue.

4. Additional members of sample group are chosen by recruiting each Nth subject (5 subject in example above) among the population.


  1. When done correctly, this method will approximate the results of simple random sampling.
  2. The selection of a sample is very convenient and is cost and time efficient. This is an aspect of systematic sampling which makes it applicable in many situations.
  3. Systematic sampling is effectively suitable in collecting data from geographically disperse cases (that do not require face-to-face contact).


  1. Systematic sampling can be applied only if the complete list of population is available.
  2. If there are periodic patterns within the dataset, the sample will be biased.
  3. If study participants deduce the sampling interval, this can bias the population as non-participants will be different from study participants.


Community content is available under CC-BY-SA unless otherwise noted.