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Sampling

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This tutorial provides an introduction to the idea of sampling. One of key thing that you need to understand about sampling is the relationship between a population and a sample. Let's start just with the definition of both of those two terms.

Your population or your population of interest is the collection of all individuals or items under consideration in the statistical study. Your key term here is all. Your population is everybody.

So if you're interested in learning how much the typical person in an office building spends on lunch, your population there would be all workers in this certain office building. So we want to consider everybody that we're interested in. So that's what going to be your population.

A sample is a subset of the population from which data is obtained. The key term here is subset. So your sample is always going to be smaller than your population. If a population is reasonably small or if considerable time and resources are available, a census can be conducted.

A census here is a collection of data taken from an entire population. If we we go back to the example of the office building and figuring out how much a typical person spends on lunch, if we wanted to answer that question using a census, we would need to go and survey every single person in the office building. If it's a small office building with only maybe 10 employees, it would be reasonable to do a census. If you're office building has 1,000 people in it, then a census is going to be very impractical.

Since most of the time it will be impractical to do a census, a sample must be used. And then the process of taking a sample is called sampling. When sampling, it's very important that a representative sample is used.

So we want our sample to represent our broader population. So a representative sample is a sample that has relevant characteristics to the population. So again going back to the office building example, it's going to be important that-- so if we have that giant office building that has 1,000 employees, it's going to be important that when we take our samples-- say we only want a sample 30 people, instead of 1,000. It's going to be important that those 30 people are a good representation of the population. So that there characteristics mimic the greater population.

All right, in their sampling procedure, they don't really go into how they came up with their sample, but in future tutorials, we are going to look at how are samples like that taken and how are they then used to help us gain more information about the population. So this idea of a population versus sample is important to the sampling process. And we'll continue looking at that in future tutorials. So thanks for watching, and we'll see you soon.