What is Systematic Sampling?

Systematic sampling is more or less a method that involves selecting various elements ordered from a sampling frame. Taking this statistical procedure starts from the random selection of elements that belongs to a list. Then every sampling interval from the frame is selected. This sampling method can only be applied if the given population is homogeneous, as these sample units are distributed systematically over the population.

It is a probability sampling method by randomly selecting sample members from the mass population at a fixed interval. This periodic interval is termed the sampling interval. It can be calculated by ascertaining the required sample sizeSample SizeThe sample size formula depicts the relevant population range on which an experiment or survey is conducted. It is measured using the population size, the critical value of normal distribution at the required confidence level, sample proportion and margin of error.read more and dividing it by population size.

How does it Work?

  • Statistically, statisticians can use systematic sampling if they want to save time or are dissatisfied with the results obtained from the simple random samplingSimple Random SamplingSimple random sampling is a process in which each article or object in a population has an equal chance of being selected, and using this model reduces the possibility of bias towards specific objects.read more method. After identifying a fixed starting point, the statisticians select a constant interval to facilitate the participant’s selection.This method must initially select the target population before selecting participants. There are various characteristics based on which identify the population and conduct the study. These desired characteristics could be age, race, gender, location, profession, and/or education level.For example, a researcher wants to choose 2,000 people from a population of 10,000 with the help of systematic sampling. He must enlist all the potential participants. Accordingly, they will select a starting point. As soon as it forms the list, every 5th person from the list will get selected as a participant, as 10,000/2,000 = 5.

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Types of Systematic Sampling

#1 – Linear

  • It terms linear since it follows a very linear path and tends to stop at the end concerning a particular population. In this type of sampling, any sample is unrepeated in the end.Also, ‘n’ units are chosen to form a part of the sample that has ‘N’ units of population. The analysts and researchers can take skip logic into use for the selection of ‘n’ units instead of randomly selecting these ‘n’ units from a given sample.A linear systematic sample selects arranging the total population and classifying the same in a sequence, selecting the ‘n’ or the sample size, calculating the sampling interval (K= N/n), randomly selecting a number from 1 to K, adding ‘K’ (sampling interval) to the randomly chosen number for adding the next member to the sample and repeating this process for adding the remaining members from the sample.

#2 – Circular

  • In this type of sampling, it is seen that the sample starts from a point where it has ended. It means the sample restarts from the point where it has ended. This type of statistical sampling method arranges the elements circularly.There are two ways to form a sample in this statistical sampling method. If K= 3, the samples will be the ad, be, ca, db and ec. Whereas if K=4, the samples are ae, ba, cb, dc, and ed.

Linear vs Circular Systematic Sampling

It tends to follow a linear path and then stop at the end of the given population. Whereas, in the case of circular systematic sampling, the sample restarts from a point where it ended. The ‘k’ in a linear systematic sampling represents sampling intervals, while ‘N’ in a circular systematic sampling indicates the total population. In the linear method, all sample units are arranged linearly before selection. In contrast, in the case of a circular method, all the elements are arranged circularly.

Advantages of Systematic Sampling

#1 – Quick

It is a quick method; i.e., it can save statisticians a lot of their time. It becomes easy for researchers and analysts to choose a sample size with the help of this approach since it is really quick. There is little need to number every member from the sample. It also helps in the faster and simpler representation of a particular population.

#2 – Appropriateness and Efficiency

The results obtained from systematic sampling are appropriate as well. As compared to other statistical methods, the results derived from the statistical method are highly efficient and appropriate.

#3 – Low Risk of Data Manipulation

The data manipulation probabilities are really low compared to other statistical methods.

#4 – Simplicity

This method is really simple. It is one of the main reasons why analysts and researchers prefer to go for this method instead of any other method. The simplicity of this method has made it quite popular amongst analysts and researchers.

#5 – Minimal Risks

The risk involved in the systematic sampling method is the bare minimum.

Disadvantages of Systematic Sampling

It becomes difficult when one cannot estimate the population size. It even compromises the effectiveness of systematic sampling in various areas, such as field research on animals. There is also a possibility of data manipulation and business since the researcher gets to choose the sampling interval.

Conclusion

  • It enables analysts and researchers to take a small sample from a larger population. This selection can be based on age, gender, location, etc. Statistical sampling is mostly used in the field of sociology and economics. It can be of two types- linear and circular systematic sampling.It could be really easy. It also gives researchers and analysts a better degree of control. It can even help in the elimination of cluster selection. This type of statistical method has a very low probability of error and data manipulation. It is simple, and thus, it is why the method is really popular and preferred by most statisticians.

This article is a guide to what is Systematic Sampling and its definition. Here, we discuss the types of systematic sampling, how it works, and its advantages and disadvantages. You can learn more about from the following articles: –

  • Stratified SamplingCluster SamplingRandom vs Systematic ErrorFormula of Sampling ErrorPoint Estimators