Statistics & Data Science
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Statistics Basics › Learning from SamplesStatistics Basics › Data and SamplingStatistics Basics › Probability and ChanceChapter 6Learning from Samples
A poll asks a thousand people and speaks for a whole country.
- How can a small sample say anything sure about millions?
- The answer is that chance, which makes every sample a little different, also follows rules.
- In this chapter you watch samples scatter, measure how far a sample is likely to miss, and turn that into an estimate with a margin of error.
- Then you test an idea: is a coin fair, does a new method help?
- Small simulations in Python do the heavy work, so you can see each idea happen before you name it.
Part of Statistics & Data Science · Essentials (chapter 6)
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Sampling Variability and Sample Size
Ask forty students how they come to school, then ask forty others. The two answers differ, and neither is wrong. Watch many samples scatter around the truth, and draw the pattern they make. Then find out how fast that scatter shrinks when the sample grows, and why a sample of a thousand works as well for a city as for a country.
Confidence Intervals for Proportions and Means
A news report says that 52% of people back a new park, plus or minus 3 points. Where do the 3 points come from, and what do they promise? Build an estimate with a margin of error, check when the formula for a proportion can be trusted, and plan the size of a survey. Then run a hundred surveys by simulation and see what a 95% confidence level really means.