Statistics & Data Science
High School (9–10)
High School (11–12)
Undergraduate
General
Statistics Basics › Data and SamplingStatistics Basics › Study Design and ExperimentsChapter 1Sampling and Study Design
A cook tastes one spoonful and decides about the whole pot.
- Every survey, poll and medical trial does the same thing with people.
- This chapter shows how a small sample can speak for a large population, and how it goes wrong when the sample leaves people out.
- You will choose samples fairly, judge the margin of luck in a poll, and design a study that can tell a cause from a coincidence.
- Every idea starts from a made-up data set or a simulation, and short Python programs do the counting.
Part of Statistics & Data Science · Essentials (chapter 1)
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Populations, Samples and Bias
A radio show asks its listeners to text in, and nine in ten say the same thing. Does the whole town agree? Meet the population, the sample, the parameter and the statistic, and see why a sample tells the truth only when it is chosen fairly. You will name the usual kinds of bias and find out why a huge biased sample is still wrong. It suits a curious student from Class 9 on, and any adult who reads polls.
Fair Ways to Choose a Sample
A head teacher wants the views of 60 students out of 1200. Should she pick names from a hat, take every twentieth name on the list, or ask a few whole classes? Learn the simple random, systematic, stratified and cluster methods, when each is used, and how Python picks a random sample. Then see why a stratified sample can beat a simple one, and how large the margin of luck in a poll really is.