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▁▃▇도수분포 Lab

A roster of 25 classmates' heights — does reading 25 numbers reveal the class?

Individual numbers stay invisible however long you read — bin them into classes and count, and the 'shape' of the distribution rises out of the pile.

Experiment

Hands-on experiment

🔮 Predict first — read the roster of 25 classmates' heights (25 raw numbers). Does the class's character show at a glance?

📋 Bin the roster

Below is the actual roster. Press to bin into 5cm classes and count.

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📖 Read more — why it exists · insights · common mistakes · formulasExpand ▾

Why

Why does this exist?

Thirty test scores, 25 heights, a thousand customer ages — data arrives as piles of individual numbers, and reading them yields no judgment.

The fix: choose intervals (classes) and count how many fall in each (frequency). As a table it's a frequency table; as bars, a histogram — the pile becomes a shape.

Once the shape shows, questions become possible: where does it cluster (center), how wide (spread), is it lopsided (skew)? Statistical thinking starts here.

Insight

Insights from the video

A histogram is the data's face.

A mean is just the data's address; the histogram shows the whole visage. Two groups with equal means can wear utterly different faces — the habit of looking at distributions is half of statistics.

Bin width is resolution.

Too narrow and you see only jagged noise; too wide and features smear away. The same data tells different stories at different widths — choosing the width IS analysis.

Misconception

Common misconceptions

Binning loses information, so it's a loss.

You lose individual values but gain the more important thing: the distribution's shape. Where the data clusters and how it spreads never shows in a roster — summarizing is translation, not loss.

The group with the taller bar has the higher share in that class too.

With different group sizes, comparing counts is meaningless. 7 of 25 (28%) beats 20 of 100 (20%) in share — groups compare by relative frequency, not frequency.

Formula

Writing it as math

What the height-roster experiment confirmed, in mathematical language.

Class and frequency

A class is a bin holding data; frequency counts what falls inside — their table is the frequency table.

Relative frequency

Frequency divided by the total — the common language for comparing groups of different sizes. Always sums to 1.

The histogram

The frequency table drawn — the bars' silhouette is the distribution's shape (bell, skew, peaks).

In Real Life

Where you meet it in real life

Score distributions

'Average 72' says little. Draw the histogram and you see whether it's twin-peaked (studied vs gave up) or bell-shaped — why teachers read distributions before averages.

Population pyramids

Two age histograms (male/female) in 5-year bins, placed back to back — aging societies read off a single shape.

Camera exposure histograms

A photo app's histogram is the frequency distribution of pixel brightness. Piled to the right means overexposed — photographers read one per shot.

Game rank distributions

An online game's tier chart is a histogram of player skill. Where you sit on the bell is your percentile.

Try Yourself

Test yourself

Q1Which heights belong to the class [155, 160)? Does 160 count?Show answer ▾

155 up to but not including 160 — 160 goes to the next class [160, 165). The 'from-inclusive, to-exclusive' agreement keeps boundary values from being counted twice.

Q2If 6 of 25 students fall in [150,155), what's the relative frequency?Show answer ▾

6 ÷ 25 = 0.24 (24%). All relative frequencies sum to exactly 1 — a built-in check.

Q3What happens to the histogram with very narrow (1cm) bins?Show answer ▾

Nearly 25 scattered, jagged bars — the shape dissolves. Too wide (30cm) and everything smears into one bar. A moderate width keeps the shape alive — width choice is part of the analysis.

💡 Try answering yourself before revealing it — getting it wrong is where learning starts.

Watch

Related video

Twenty-five numbers, one picture — frequency distributionsThe video link is coming soonBrowse the YouTube channel →

Connection

Concepts connect

Previous concept

Averages

Feel one number's limits (the mean) and the need for shape (distribution) appears.

← Averages lab

Leads to next

Box Plots

Another portrait — summarizing a distribution in five numbers instead of the full shape. The weapon of group comparison.

Go to the Box Plots lab →

Related

Labs worth exploring together

Related lab

Averages

Summarizing the center in one number — complete only alongside the shape.

Go to the Averages lab →

Related lab

N(0,1)

Distributions

Smooth the histogram and the normal curve emerges.

Go to the Distributions lab →