Systematic Sampling vs Random Sampling

What is systematic sampling?

Systematic sampling is a type of probability sampling method where samples are selected from a population at a fixed periodic interval. For example, selecting every 10th household in a neighborhood is a best example of this .

What is random sampling?

Random sampling is a technique where samples are selected from a population entirely by chance, with each member of the population having an equal probability of being chosen.

Which one is easier to implement?

Systematic sampling is generally easier to implement than compared to random sampling because it does not require generating random numbers or a random starting point. So thus it is very easy.

Which one is more likely to be biased?

Systematic sampling has a higher risk of introducing bias if there is a hidden periodic pattern in the population that corresponds to the sampling interval. Random sampling is less likely to be biased if done correctly.

In statistical research, the two most prevalent approaches for selecting samples from a population are systematic and random sampling. Each method has advantages and disadvantages, and the decision between them is determined by a variety of factors such as the population’s characteristics, research aims, and available resources. In this article, we will learn in detail about difference between systematic sampling and random sampling along with basic introduction about them.