Random sampling: cluster sampling

Written by Carlos Ochoa el 25 de January 2017

With this post dedicated to cluster sampling, we conclude our first block of posts on random sampling. With our next post, we will launch into nonrandom sampling methods, which are used most commonly in online research.


Cluster sampling is a method that makes the most of groups or clusters in the population that correctly represent the total population in relation to the characteristic that we wish to measure. In other words, all of the variability that exists in a population is contained within the population. When this is the case, we can select just a few of these clusters to conduct our study.

Let’s look at this method from another point of view. In most of the methods we’ve seen so far, the sampling units have coincided with the units to be studied (individuals). With cluster sampling, however, the sampling units are groups of units to be studied, which can be very beneficial when it comes to minimizing the cost of the sampling process. Of course, there’s a trade-off: this technique usually entails less precision, since there is a lack of heterogeneity among the clusters.

Category: random sampling | cluster sampling | sampling

Random sampling: systematic sampling

Written by Carlos Ochoa el 23 de January 2017

Now that we have taken a look at stratified sampling, we’d like to continue our series of posts on sampling techniques by examining systematic sampling.

Systematic sampling used to be very popular, before computer science solved one of researchers’ biggest headaches: randomly selecting individuals from within a sample. Now that computers can generate random numbers, this problem has vanished.

It is still used, however, to select individuals over a period of time. For example, if we want to study satisfaction with a service at a store, we can systematically survey one out of ever n customers who visit. In these cases, in which the variance between individuals could be different at different moments, systematic sampling can be even more precise than pure simple random sampling.


Category: online sample | random sampling | sampling

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