Systematic sampling is a method of probability sampling where every kth individual or element is selected from a list after an initial random start. The key characteristic of systematic sampling is the systematic and equal spacing between the selected elements. This method is useful when researchers want to ensure a representative sample while maintaining simplicity in the selection process.
Two important features of systematic sampling include:
- Regular interval: Individuals or elements are selected at regular intervals from a list. The interval is determined by dividing the total population size by the desired sample size (k = N/n, where N is the population size and n is the sample size).
- Random start: The process begins with a random start, meaning that the first individual or element is selected randomly from the first k individuals on the list. Subsequent selections occur at equal intervals.
Some advantages of systematic sampling are:
- Simplicity: Systematic sampling is easier to understand and implement than other probability sampling methods.
- Efficiency: Systematic sampling can be more efficient than simple random sampling when a complete list of the population is available.
- Representativeness: When the list is randomly ordered, systematic sampling can provide a representative sample, ensuring that different population segments are included.
Some disadvantages of systematic sampling are:
- Risk of bias: If there is a hidden pattern or periodicity in the population list, systematic sampling may introduce bias.
- Dependence on list quality: The effectiveness of systematic sampling relies on the quality of the list or sampling frame. If the list is not well-organized or has a specific pattern, it may affect the randomness of the sample.
- Potential for skewing: If the list is ordered in a way that aligns with the periodicity of the sample interval, the sample may not be as representative as intended.
- Limited flexibility: Systematic sampling may be less flexible in cases where the population list is unavailable or difficult to obtain.
List of recommended resources #
For a broad overview #
Systematic Sampling | A Step-by-Step Guide with Examples
This blog on Scribbr gives a broad overview of systematic sampling, a type of probability sampling method. The blog details the various steps for conducting systematic sampling on a population sample.
The complete guide to systematic random sampling
This article on systematic random sampling by Qualtrics XM highlights the method of systematic random sampling and how to create random sampling surveys to create them.
For in depth understanding #
Chapter 11 Systematic Sampling
This module by IIT Kanpur gives an in-depth understanding of systematic sampling. It also provides a comparison of systematic sampling with stratified sampling and simple random sampling with a linear trend.
Recent developments in systematic sampling: A review
This article by Sayed A and Ibrahim A provides a review of the recent work done in the area of systematic sampling as well as offers some recommendations to survey practitioners using the systematic design for various sampling situations.
Case study #
An epidemiologic study of occupational stress factors in Mumbai police personnel
This study highlights some of the occupational stressful factors in the police organization, focusing specifically on Mumbai police. The study adopts the techniques of simple and systematic random sampling for collecting data.
Computing the Average Body Mass Index: A Study with Systematic Sampling Using Auxiliary Information
This research article by Gajendra K. Vishwakarma, Neha Singh and Surendra P. Singh presents a method to estimate the body mass index using the measures of different body parts. The method of estimation for the mean of the study variable under systematic sampling using auxiliary information has been used to estimate the body mass index (BMI).
References #
7.1 – Introduction to Cluster and Systematic Sampling
What’s the Difference Between Systematic Sampling and Cluster Sampling?
