Systematic Sampling, PDF

What Is Systematic Sampling?

Systematic sampling is a valuable probability sampling method in which researchers choose and collect a random sample from a broader population with a fixed periodic interval or sampling interval based on the calculation when they divide the population size by their preferred sample size.  Most researchers and analysts use this method because of its efficiency and simplicity as it can be accomplished in a flash and it has a low risk of data manipulation.  It is a clear and straightforward survey methodology recommended for researchers who have budget constraints, who are required to complete projects within a short time, who don’t have any patterns in their data analysis report, who prefer to reduce the risk of poor data quality, and who need to develop multiple samples due to the increasing population sample size. 

According to a research report, almost 55% of internet users live in the Asia Pacific region, the fastest-growing region, and can be a fantastic opportunity for survey researchers to understand the market and the customers’ needs. Also, the largest market in 2021 for online survey services is in North America. That’s why many business firms and organizations use online surveys and survey reports and integrate them into systematic samplings so that they can decipher the success of their products or services and assess the needs of their target consumers. 

Types of Systematic Sampling

Systematic sampling is a probability sampling method that can be easily implemented whenever a certain population can be listed in order or it encompasses a definite spatial area. It may be classified into three major types that you can use to produce a systematic sample: linear systematic sampling, circular systematic sampling, and repeated systematic sampling.

1. Linear Systematic Sampling

In this sampling method, researchers can’t repeat samples at the end as they use a skip pattern which is made following a linear path rather than randomly choosing the sampling interval. If you need to construct a linear systematic sample, arrange the population in a classified sequence, identify the sample size, and then calculate the sampling interval. After that, choose a random number between 1 and the sampling interval, and continue adding new members of the population linearly until you reach the desired sample size.

2. Circular Systematic Sampling

From the name itself, circular systematic sampling begins to sample again from the same point where it once ended. This sampling technique treats the audience as a circular list or similar to a clock with the hour lines representing the intervals. Use a circular systematic sampling if you have a large population to draw from or you need multiple sets of samples to deal with. 

3. Repeated Systematic Sampling

This type of probability survey methodology involves the selection of diversified samples from the target population and combining them into a single systematic sample. Typically, researchers select smaller systematic samples using multiple random starts instead of only one random start. Despite being more time-consuming than linear systematic sampling, repeated systematic sampling decreases the effect of bias because of periodicity, a frequently occurring pattern in the sampling frame. Thus, it offers more than one cluster of elements and expedites the calculation of variances and standard error of estimates from the sample. 

Benefits of Systematic Sampling

There are many uses of systematic sampling such as in forest and land use community surveys, in a population census to obtain information on supplementary questions, in geological mine sampling, in household surveys, in industrial sampling, in record sampling, and in quick tabulation and in the estimation of non-sampling errors in census work. What are the major benefits of using systematic sampling? 

Simplicity: Systematic sampling showcases simplicity in terms of generating the most authentic and significant outcomes. Researchers use this probability sampling because it is widely considered to produce desirable quality data when they perform research. Practicality: This sampling technique for survey research enables the researchers to produce a random sample population with an all-inclusive and randomized data set in seemingly any circumstance where the prerequisites are reached. Plus, systematic sampling is typically among the most affordable and budget-friendly sampling methods among other sampling methods. Random Probability: It allows the researchers to create a randomized group of people. Random probability is a crucial factor to attain valuable results statistically. Clarity: Systematic sampling is generally favored by the majority of researchers and analysts because it is easy to perform and easy to comprehend. It provides more clearer and detailed information about the systematic samples. Low Chance of Data Manipulation: If you are working on certain data management and analysis projects, conduct systematic sampling because it is a method with a low risk of data alteration and manipulation. No need to worry about inaccuracy in your data from your survey research work when you apply this sampling method properly.

How to Create a Systematic Sample

A systematic sample may be used for some subsequent events such as to constitute a rotating panel design group and to make the core of a panel survey with supplementary units included in the sample from time to time. Follow the steps we provided in this section to create a systematic sample for your statistic project and survey research work.

Step 1: Identify the Target Population and Sample Size

Use a systematic sampling method to identify and define the entire target population sufficiently before you prepare a population sample. For example, if you are a business owner or manager, include previous customers at your shop when you sample your target population. Or if you are assigned to the marketing team for a new product launch, sample the population at large or sample a particular group of people according to their ages, demographics, geography, and many others. Then, determine the population size and the ideal statistically significant sample size.

Step 2: Designate a Number to Every Member of the Population

Assign every member of the broader population a specific number. It is a simple step, especially if the population is already organized in a random way n alphabetical arrangement. If it is not still organized, randomize the population before the numbering.

Step 3: Decide the Fixed Periodic Interval

Calculate the fixed periodic interval or sampling interval when you divide the total population by the number of people you plan to incorporate in the survey. After that, select a starting point or choose a random number. For instance, select a random number between 1 and 100 to help you determine your starting point.

Step 4: Prepare the Survey

When you’re done determining your starting point, now is the right time to complete the systematic sample. Finally, prepare your plan to start the survey research work.

FAQs

What are the common types and techniques of probability sampling?

Some of the popular probability sampling types and techniques are simple random sampling, cluster sampling, convenience sampling, systematic sampling, stratified sampling, purposive sampling, and snowball sampling.

Why is sampling essential in research work?

It is actually impossible to conduct research and study the entire target population. Sampling is essential because it allows the researchers to draw conclusions from the collected samples.

Where is systematic sampling used?

Researchers and data analysts use systematic sampling when there exists a low risk or a low possibility of data manipulation. It is preferably used over simple random sampling in this case study. 

What is the difference between systematic sampling and simple random sampling?

Systematic sampling is a method that allows you to select a specific data point per each predetermined interval. It is more accurate than simple random sampling whenever the variability within the prospective samples is higher than the variability within the population units. On the contrary, simple random sampling is a method that enables you to choose each data point with equal probability. 

Is systematic sampling qualitative or quantitative?

Systematic sampling is mostly used in quantitative research and quantitative data analysis as it focuses on survey research and population units.

What type of sampling is used in quantitative and qualitative research?

Convenience sampling is the sampling method used in both quantitative and qualitative research, especially when conducting business studies. 

How accurate is systematic sampling?

This type of probability sampling method for survey research is on average twice as accurate as random sampling with one point per block. 

What are the different types of systematic sampling?

The different types of systematic sampling are linear systematic sampling, circular systematic sampling, and repeated systematic sampling.

What is the difference between systematic sampling and cluster sampling?

Systematic sampling is a sampling method used by researchers to choose a random starting point from the population and a sample is collected from regular fixed intervals of the population. While cluster sampling is a sampling method in which researchers divide the population into clusters and gather a simple random sample from each cluster.

What are the benefits of systematic sampling?

Researchers and analysts use systematic sampling because it is simple to conduct and the methods or the process to accomplish it is easy to understand. It offers a next-level degree of control than other sampling techniques. Plus, it has a low-risk factor when it comes to having inaccurate data.  

As a generally used probability survey sampling technique, systematic sampling is very efficient and more convenient because it is not subjected to restrictions. When you conduct systematic sampling for your survey research, create a definite audience, figure out what size will be appropriate for the sample, designate a number for each participant or subject, and calculate your sampling interval. Sample.net offers an extensive template selection for systematic sampling, cluster sampling, stratified sampling, and other probability sampling methods that you can easily download and use for your survey research and data analysis work.