Systematic sampling is a type of sampling method that involves selecting a smaller group of participants (the sample) from a larger group of participants (the population). However, this method of sampling recognizes that selecting the sample randomly can lead to inefficiencies. So, it adds a fixed, periodic interval, determined prior to sampling, with which people will be selected. It’s not as confusing as it sounds! In this blog, we’ll look at how systematic sampling works, provide examples of this type of sampling method, and look at the pros and cons.
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Systematic Sampling Definition
Systematic sampling is defined as “a type of probability sampling method in which sample members from a larger population are selected according to a random starting point but with a fixed, periodic interval.” We call this interval the sampling interval.
It’s worth noting that along with the “classic” systematic random sampling above, there is also linear systematic sampling in which a skip pattern is created following a linear path rather than using a sampling interval, and circular systematic sampling, in which a sample starts again at the same point after ending. For the purposes of this blog, however, we will continue to focus on systematic random sampling.
Example of Systematic Sampling
Want to see this sampling method in action? Here is a look at the six systematic sampling steps with a real-world example.
1. Identify Your Population. This is the group from which you are sampling.
You are a small business owner with 2,000 customers. This is your population size.
2. Assign Numbers to the Population. In this step, you give every member of the population a number.
You put your customer list into a spreadsheet and number them from 1 to 2,000.
3. Determine Your Sample Size. Sample size is how many people from the total population you will survey.
Because you don’t have the time or money to survey all 2,000 customers, you choose to survey 10% of them, or 200. This is your sample size.
4. Determine Your Sampling Interval. To do this, divide the population size by the desired sample size.
In our example, 2,000 / 200 = 10. This means you would survey every tenth person from your total population of 2,000.
5. Choose a Starting Point. To be sure the sampling is random, choose a number between 0 and your sampling interval.
You can select a number between 0 and 10, and choose 7. This is your starting point.
6. Identify Sample Members. Now that you have your sampling interval and starting point, you can get started!
Selection begins at 7, and then every tenth person is selected from there (7, 17, 27, 37, and so on). For this reason, systematic sampling may also be referred to as systematic random sampling.
Systematic Sampling Advantages and Disadvantages
Systematic sampling is popular with researchers because it is easy to conduct and is less likely to introduce survey bias into the sample. Of course, there are also a few drawbacks.
Five Pros of Systematic Sampling
Systematic sampling can be used whenever you want the benefits of randomly sampling the population you’re studying. It can be especially useful in situations where you don’t have details of the entire population before you begin your study. This is because systematic sampling is rule-based, so you can just apply the interval you’ve chosen to the data.
1. Ease to Use and Understand
First and foremost, systematic sampling is quite simple to conduct, making it a favorite for researchers. Plus, this method’s central assumption – that the results represent the majority of normal populations – helps to guarantee that the entire population is evenly sampled.
2. Quick and Cost-Effective
The way systematic sampling is structured makes surveys easy to create and the data easy to analyze. This type of sampling is also effective when the budget is right because the sample selection process is relatively straightforward with no further research needed at the outset.
3. Semi-Controllable Selection Process
Although systematic sampling is random, with researchers having to select a sampling interval and starting point, it’s not “excessively random” like simple random sampling, another method of sampling which is conducted completely by chance, for example, literally choosing names from a hat.
4. Low Risk of Data Contamination
With systematic sampling, the risk of data contamination is inherently low because of the even distribution of members to form samples. Plus, the only random component of the sample is the selection of the starting point. From there on, the process moves in a set pattern until the sample is complete. However, if there is a chance that the researchers can manipulate the interval length to arrive at a desired conclusion, choosing a simple random sampling technique would be the better option.
5. Low Risk of Bias
Because the selection process is random, there is little chance of sampling or survey bias – with some exceptions, for example, when the sample has some sort of repeating pattern. Let’s say you’re looking at a classroom list of students with “boy, girl, boy, girl” ordering. If the sampling interval is two, the sample may introduce gender bias, greatly skewing survey results.
One Drawback of Systematic Sampling
One main disadvantage to the systematic sampling approach is needing to know the size of the population. Without this information, this technique has flaws. The good news is that systematic sampling still works if you are ready to guess the interval.
For example, a film company wants to survey theatergoers about a new movie. Although they don’t know how many people will attend the screening in advance, they can choose to survey every fifth person leaving the theater. Then, the true population size will be approximately five times the size of the sample.
Systematic Sampling with Online Image Surveys
As with any survey, to improve your response rates to avoid having to find a new systematic sample, consider using online surveys with photos. With SurveyLegend, our picture surveys boost engagement, help trigger respondent emotion and memory, and cross language barriers.
Below is an example of one of our photo surveys, designed to match the small business survey/sampling scenario we highlighted earlier. You can also create polls with pictures, questionnaires with images, and much more.
Conclusion
Systematic sampling, or systematic random sampling, is a quick, easy, and effective way to survey smaller subsets of a large population at random and without introducing survey bias. Whether you go with this type of sampling or another technique, we’ve got you! SurveyLegend lets you start for free, and has dozens of beautiful and responsive online survey templates from which to choose.
Do you use systematic sampling when surveys? Is there another method of sampling you prefer, and if so, why? Let us know in the comments!
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Frequently Asked Questions (FAQs)
Also known as systematic random sampling, this is a type of probability sampling method in which a subset of a larger population is selected according to a random starting point but with a fixed, periodic interval.
This sampling method is generally easy and inexpensive. The risk of data contamination and sampling bias is also low compared to other sampling techniques.
There are three main types: systematic random sampling (the most popular), linear systematic sampling, and circular systematic sampling.
