Statistics · Statistical sampling
Chapter 1 · 4
The idea
Populations, samples and the large data set
What a population, a census and a sample actually are; the sampling units and the sampling frame; why you would sample rather than take a census (and when a census is impossible); and how a sample can be unrepresentative — including the trap of combining overlapping samples.
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Statistics · Statistical sampling
Populations, samples and the large data set
What a population, a census and a sample actually are; the sampling units and the sampling frame; why you would sample rather than take a census (and when a census is impossible); and how a sample can be unrepresentative — including the trap of combining overlapping samples.
Why it works
Population, sample, census
Statistics starts with a simple split: the population is the whole set of things you care about — every member of it — and a sample is a subset you actually look at. If you were studying the heights of all Year 12 students in a school, the population is every Year 12 student there; a sample might be 30 of them.Census: everyone, at a price
A census observes every member of the population. It is completely accurate in principle — you've missed no one — but it is often expensive, slow, or simply impossible:- Cost and time. Asking all 30 million voters, or measuring every tree in a forest, is huge.
- Destructive testing. To find how long a make of lightbulb lasts you have to run bulbs until they fail. A census would destroy the entire stock — there'd be nothing left to sell. Here you must sample.
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The rest of the explanation, plus 3 worked examples you step through move by move.
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