## What is Systematic Sampling?

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

This is a method where probability sampling is performed by randomly selecting sample members from the mass population at a fixed interval. This periodic interval is better termed as the sampling interval and it can be calculated with ascertaining the required sample size and dividing the same by the size of the population.

### How does it Work?

- Systematic Sampling can be used by statisticians in case they want to save time or are dissatisfied with the results obtained from the simple random sampling method. After the identification of a fixed starting point, the statisticians select a constant interval for facilitating the participant’s selection.
- In this method, initially, the target population needs to be selected even before the selection of participants. There are various characteristics on the basis of which the population is identified and the study is conducted. These desired characteristics could be age, race, gender, location, profession, and/or education level.
- For example, a researcher wants to choose 2000 people amongst the population of 10,000 people with the help of systematic sampling. He must enlist all the potential participants and accordingly a starting point will be selected. As soon as this list gets formed, every 5th person from the list would be selected as a participant, as 10,000/2000 = 5.

### Types of Systematic Sampling

#### #1 – Linear

- This termed linear since it follows a very linear path and tends to stop at the end with respect to a particular population. In this type of sampling, any sample is not repeated 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 is selected by 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. This means the sample restarts from the point where it has actually ended. In this type of statistical sampling method, the elements are arranged in a circular fashion.
- There are particularly two ways to form a sample in this type of statistical sampling method. If K= 3, then the samples will be the ad, be, ca, db and ec whereas, if K=4, then 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 actually ended off. The ‘k’ in a linear systematic sampling represents sampling intervals while ‘N’ in a circular systematic sampling indicates denotes total population. In the linear method, all the sample units are arranged in a linear fashion before the selection process while in the case of a circular method, all the elements are arranged in a circular fashion.

### Advantages of Systematic Sampling

#### #1 – Quick

This is a quick method i.e. it can save statisticians a lot of their time. It becomes really easy for researchers and analysts to choose a sample size with the help of this approach since it is really quick. There is a negligible need to number each and every member from the sample and this 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 probabilities of data manipulation are really low as compared to other statistical methods.

#### #4 – Simplicity

This method is really simple. This 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 amount of risk involved in the systematic sampling method is the bare minimum.

### Disadvantages of Systematic Sampling

This becomes difficult when the population size cannot be estimated. This 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 on the basis of various factors like age, gender, location, etc. Such 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 and 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.

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