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The systematic random sampling is also a probabilistic sampling technique that is used to select samples for a study. Just like the simple random sampling technique, samples are selected randomly which means that all members of the population have a fair chance of being selected to take part in the study.

The systematic random sampling also has the attribute of ensuring that the various characteristics of a population of the study are fairly represented and captured in the selected samples.

The difference between simple random sampling and systematic random sampling lies in their approaches. While the simple random uses approaches such as dice-casting, balloting, coin-tossing, etc., systematic sampling uses the approach of selecting samples based on a choice of either odd or even numbers, and the selection of samples at intervals of a chosen number (say 5 for example).

While using the odd or even number to select samples for a study, the researcher will first of all gather the whole population and give them numbers. Thereafter, he will tell those who by chance received the predetermined category (let's say even numbers for example) to wait and take part, while he will discharge those who were given a odd numbers. So, those who received even numbers become the participants of his study.

In the use of a predetermined number interval, samples are selected at a predetermined number. This means that members of the target population who fall on the predetermined number interval become samples of the study. For example, if the predetermined number is five, the researcher will consistently count members of the population from one to five. Every member counted as number five in the whole population will take part in the study.

The selection of samples using the systematic sampling is based on luck, and this underscores the importance of the fairness of nature (Adegoke, 2011)

Footnote:
Adegoke said 'nature is fair while teaching sampling to the M.Ed students in the year 2011. Late Benson A. Adegoke was a professor of Mathematics Education and Educational Evaluation at the Institute of Education, University of Ibadan.

Abimbola Wilson Awotedu
Senior Research Fellow

Simple random sampling is a technique used in the selection of samples for a research study. It is a probabilistic sampling technique because the selection of samples is done at random, which means that every element in the population has a fair opportunity of being selected as a sample for the study.

Simple random is usually used when a researcher knows the total number of the target population and has unhindered access to them. For example, simple random sampling can be used to select students and/or teachers in a school for a study. Also, simple random sampling can be used to select patients in a medical facility to observe the effectiveness of a newly manufactured drug.

Simple random sampling can be conducted using various strategies. It could be done through balloting, dice-throwing, coin-tossing, etc. The underlying principle is that the selection of samples is done randomly and not influenced by the researcher's bias.

Using this sampling technique gives every member of the population an equal opportunity to be chosen to take part in the study. It is a technique that shows the unique attribute of nature as being a fair element (nature is fair). It is basically determined by 'luck'.

This sampling technique is very useful in conducting experimental studies as it is capable of reducing systematic and error variance. It also ensures that all elements within the population are given a supposedly fair representation in the study.

Abimbola Wilson Awotedu
Senior Research Fellow
XYZ-Intellectuals