High School Statistics

Slices of a circle — each one a percentage of the whole.

Bar, pie, line — the same numbers told three ways.

Compare categories at a glance — taller bar means bigger.

Connect points to track change over time.

Pictures stand in for counts — friendly charts for small data.

Bar charts for grouped numerical data — bins on the x-axis.

One dot per data point — see exactly where each value lands.

The fastest way to count by hand — strokes in groups of five.

How often each value (or range) appears — turn a list into a table.

Running total — and the curve it builds.

Two variables, one dot per data point — patterns appear.

An old-school way to see distribution without losing the actual numbers.

Design good questions, gather honest answers, analyse the results.

Mean, median, mode, range — interactive.

Add them all, divide by how many — the everyday average.

Some data points count more — multiply, then divide by total weight.

On average, how far is each value from the mean?

The middle value when sorted — robust against outliers.

Branch out the possibilities — multiply along, add across.

P(A given B) — once you know B happened, A's chances change.

P(not A) = 1 − P(A). The 'everything else' rule.

Roll dice and flip coins as many times as you like.

One coin flip doesn't affect the next — multiply their probabilities.

Can't both happen at once — add their probabilities.

Update your beliefs when new evidence shows up.

Just 23 people — and there's a 50% chance two share a birthday.

On average, how far is each value from the mean?

Add them all, divide by how many — the everyday average.

Some data points count more — multiply, then divide by total weight.

The middle value when sorted — robust against outliers.

The value that appears most often.

Largest minus smallest — the simplest spread.

Range, IQR, standard deviation — how spread out is the data?

Split sorted data into four equal groups — Q1, Q2 (median), Q3.

The 90th percentile means 90% of values fall below — used for ranks.

The typical distance of a value from the mean — spread, summarised.

Data points way outside the pack — notice them, investigate, decide.

The bell curve — why so much of the world clusters around an average.

Mean 0, SD 1 — the bell curve everyone calibrates against.

How lopsided is the distribution? Tail to the left or right.

Wrap a margin of error around an estimate — and quantify your trust.

Test whether observed counts match what you expected.

Compare means with small samples — the workhorse of stats.

Pick a small group to learn about a big one — without bias.