Statistics and Data Literacy
The handful of ideas you need to read the numbers in news and reports without being fooled, each one drawn as an animated diagram you step through.
For anyone who reads news, reports or health headlines and wants to know which numbers to trust. No formulas to memorise and no software: every lesson has an animated diagram you step through, built on one small, concrete example. You start with what an average hides and how spread and the bell curve describe the rest, move on to how a poll of a thousand people can speak for millions and why two things rising together don't prove one causes the other, then meet the classic traps: ignored base rates, percentages mistaken for percentage points, and charts with cut axes. You finish by reading p-values and studies in plain words, and by running a real headline through a short checklist of your own.
By the end you can
- Choose between mean, median and mode for a real figure, and say what the spread and the bell curve add to it
- Explain how a random sample and its margin of error let a poll of about a thousand people describe a whole country
- Spot the classic traps: correlation sold as causation, ignored base rates, percentages confused with percentage points, and misleading charts
- Read a p-value and a study in plain words, and check a news headline with a short list of questions
Describing data
- Mean, median and mode: three kinds of average
Three honest ways to say what is typical, and why one very large number can drag the mean far from where most people are.
- Spread: what the average leaves out
Two places with the same average temperature can feel nothing alike; range and standard deviation measure how far values wander from the middle.
- The bell curve
Why so many measurements pile up in a bell shape, and the 68-95-99.7 rule that tells you how unusual a value is.
From a few to everyone
- Sampling: tasting the soup
How a small random sample can describe millions of people, and why a huge sample picked the wrong way can't.
- Margin of error: the plus-or-minus
What '52%, plus or minus 3' really means, why a thousand people is usually enough, and when a lead in a poll is no lead at all.
- Correlation is not causation
Two things rising together can mean one causes the other, the reverse, a hidden third cause, or pure coincidence; here's how to tell.
Numbers that mislead
- Base rates: the number people forget
Why a positive result on a '90% accurate' test can still mean you are probably fine, worked out on a grid of 1,000 people.
- Percent or percentage points? Relative and absolute risk
Going from 2% to 3% is one percentage point but a 50% rise; learn to hear which one a headline is using and to ask for the real numbers.
- Charts that mislead
Cut-off axes, stretched scales, cherry-picked dates and pictures that grow in two directions: how a true number can be drawn to tell a false story.
Reading the evidence
- P-values in plain words
A p-value asks one question – how surprising would this result be if nothing were going on? – and it doesn't answer the questions people usually think it does.
- Reading a study
Randomised trials, observational studies and everything in between: what makes a study strong, and the warning signs in how it's reported.
- Putting it together: reading a headline
One realistic headline, taken apart with the whole course: which average, what sample, what kind of study, relative or absolute, and how it was drawn.
Keep it, don't just read it
Pathwise brings each idea back just before you'd forget it, with a quick question. Free on Android and on the web, in English and Persian.