Statistics · Sampling
Chapter 1 · 4
The idea
Populations & samples
What a population and a sample are and why we sample at all; why a representative sample matters more than a big one; and the two calculations that earn the marks — scaling a sample up to estimate a population total (including capture–recapture and its assumptions) and sharing a stratified sample out in proportion.
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In this lesson — start anywhere
Statistics · Sampling
Populations & samples
What a population and a sample are and why we sample at all; why a representative sample matters more than a big one; and the two calculations that earn the marks — scaling a sample up to estimate a population total (including capture–recapture and its assumptions) and sharing a stratified sample out in proportion.
Why it works
Population, sample, census
The population is everything you want to know about — every battery in the day's production, every fish in the lake, every member of the club. A sample is a subset of it that you actually look at. Counting the whole population is a census, and it is the accurate option, so the first question is: why would anyone ever settle for a sample?Why sample at all
Three reasons, and exam questions turn on all three. Cost — asking 40 000 people costs vastly more than asking 400. Time — a survey that takes a year answers a question you needed settled in a month. And destructive testing — to find how long a battery lasts you must run it flat, so a census of lifetimes destroys the day's production. In that last case a sample isn't the cheap option, it is the only option.Keep reading — free
The rest of the explanation, plus 3 worked examples you step through move by move.
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