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Differences between a sample and a population

How do those relate to each other?

Before diving into the statistic pool, we should get accustomed to a couple of technical terms from that fascinating world. They will help us to better understand what we are doing.

  • population - a collection of things from which we collect data. It is the group we are interested in, which we wish to describe or draw conclusions about;

  • sample - a subset of a larger group (the population). Studying the sample should hopefully let us draw valid conclusions about the population.

In other words, the population includes all objects we want to study, whereas the sample is only a portion of the population. We usually don't work with the full population, due to several reason. The population can be large, and it is often impossible to get data for every object we're studying.

We talk about statistical inference when we use the sample to make generalizations about the whole population.

Sources - Statistics: Introduction (link)
Stat Trek - How to Measure Variability in a Data Set (link)