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Systematic Sampling: Capturing the Essence of Comprehensive Researc

The Ultimate Guide to Systematic Sampling

Get a step-by-step guide for choosing the correct representative sample for survey research.


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What is Systematic Sampling?

There are different methods of selecting a sample group for a research. The two broad categories of sampling are non-probability sampling and probability sampling. Systematic sampling can be categorized under probability sampling, which means that everyone in the target population has an equal chance of being selected. For example, if the population is 100, each element in this population has a 1/100 probability of being selected to be a part of the sample group.

Systematic sampling involves the choosing of a specific interval, to use it to select the sample group from within the target population. 

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What is the definition of Systematic Sampling?

Systematic Sampling can be defined as a method of probability sampling in which a researcher chooses a random starting point and a sample interval with which the sample group is selected from the target population.

How to implement Systematic Sampling in your research?

These are the two main steps required to implement systematic sampling:

  1. Divide the size of the target population “N” by sample size “n” to calculate the sampling interval “i”. If this value is in decimals, it must be rounded to the nearest whole number/integer.
  2. Then, a random starting point, “r”, may be chosen from where the sampling interval “i” is used in order to choose respondents from the target population. Before selecting the sample group, researchers must ensure that the list of the sample frame is not organized in a cyclical or periodic way in order to avoid selecting a biased sample group.

Researchers use systematic sampling via market research tool or social research software, wherein, the panel manager allows you to create a systematic sample of your choice. Voxco survey platform equips researchers with required tools to carry out their survey research efficiently.

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Example of Systematic Sampling

If a study has a target population of 1000 people, and wants to choose 25 people for its sample group (sample size of 25), we will calculate the sampling interval like so:

Target population, or N = 1000

Sample size, or n = 25

Sampling interval, or i  = N/n = 1000/25 = 40

Therefore, our sampling interval in this case will be 40, hence every 40th element in succession will be chosen from the sampling frame to be a part of the sample group.

We must also pick a random point “r” from which we may start picking elements. Let’s say we were to pick the number 17. Then, 17, and every 40th element to follow will be picked from the target population of 1000.

Types of Systematic Sampling

There are three main types of systematic sampling:

  1. Systematic Random Sampling
  2. Linear Systematic Sampling
  3. Circular Systematic Sampling

The following is a breakdown of how each type is executed:

Systematic Random Sampling:

This is the most basic type of systematic sampling and these are the steps taken to conduct it:

  • Calculate sampling interval using the formula i = N/n
  • Pick a starting point “r”. This point must be between 1 and the number of the sampling interval (between 1 and i). For instance, in the example shown above, the sampling interval is 40 so we must pick a number between 1 and 40.
  • Using the sampling interval, choose successive elements until the desired sample size is reached.

Linear Systematic Sampling:

This type of sampling employs a “skip method” whilst choosing the sample group. The skip or sampling interval is “k”, where k = N/n. These are the steps to select the sample group using linear systematic sampling:

  • Create a sequential list of the target population/population units.
  • Decide on a sample size “n”.
  • Compute the “skip” (sampling interval) using the formula: k = N/n
  • Choose a random number “r”, between 1 and k (sampling interval).
  • Add “k” to “r” to select a second unit, and continue doing so to select as many units required in the sample size.

Circular Systematic Sampling:

In this method of sampling, a sample starts again from the point it ends. The following steps can be used to select elements using circular systematic sampling:

  • Calculate the sampling interval using formula of “k”, k=N/n
  • Choose a random start “r” between 1 and N
  • Using the sampling interval “k”, skip through the circle to select units until “n” number of units are selected.
  • This method allows for “N” number of samples being selected rather than just “k”.

What are the advantages of Systematic Sampling?

  1. Easy to employ when a clear sampling frame is available.
  2. Easy to understand compared to some other types of sampling methods, such as stratified random sampling, for instance.
  3. Organized method of sampling: compared to some other types of sampling, systematic sampling is more organized which can make the process of choosing the sample group easier and less challenging. See how you can make sampling an easy task. 
  4. The risk factor for bias is minimal when the list of the sample frame is ordered in a random manner.

Disadvantages of Systematic Sampling

Systematic bias due to cyclical list of sample frames:

If the list of the target population is not organized in a fully random manner, the selected sample group may be biased, creating systematic biases in the study and its results.

Risk of data manipulation:

This method of sampling may allow researchers to be biased by giving them the leeway to construct their own systems in order to make their study produce a certain desired outcome.

Lack of randomization:

Compared to some other types of probability sampling, such as simple random sampling, this method lacks a natural degree of randomness and runs a higher risk of similar sampling units being selected.


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