The Ultimate Guide to Systematic Sampling
Get a step-by-step guide for choosing the correct representative sample for survey research.
SHARE THE ARTICLE ON
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.
Download the guide to understand step-by-step process of selecting the best sample for your next survey research
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.
These are the two main steps required to implement systematic sampling:
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.
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.
There are three main types of systematic sampling:
The following is a breakdown of how each type is executed:
This is the most basic type of systematic sampling and these are the steps taken to conduct it:
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:
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:
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.
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.
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.