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Primary - Stage 3 (Year 5 & 6) Stage 3 (Year 5 & 6) Data

Identify bias & misleading data; pose questions

20 practice questions 0 video lessons Theory + worked examples
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Theory

Data can mislead when a graph is drawn unfairly or a sample is chosen badly. Check that the scale starts at \(0\), the graph is labelled, and the sample is large and represents everyone.

Data misleads when a graph is drawn unfairly or a sample is chosen badly, even though the numbers are correct.

A fair column graph starts its scale at \(0\), rises in equal steps, has a title and labels both axes.

Cutting the scale so it starts above \(0\) makes small differences look far bigger than they are.

A survey is fair only when its sample is big enough and represents everyone, and the question does not lead the answer.

The same data on an honest and a misleading scale Two column graphs of the same four values 82, 84, 86 and 88. On the honest graph the scale starts at 0 and the columns look almost the same height. On the misleading graph the scale starts at 80 and the columns look very different, like a staircase. 050100 Scale from 0 (honest) 808590 Scale from 80 (misleading)
The same four values (\(82, 84, 86, 88\)) on both graphs. Cutting the scale at \(80\) makes a gap of only \(6\) look like a huge difference.

Check three things before trusting a graph or a survey.

CheckFairUnfair
Scalestarts at \(0\)cut off above \(0\)
Labelstitle and axesmissing
Samplelarge, mixedtiny or one-sided
The numbers do not change — only the picture. A cut-off scale is honest data drawn to trick the eye.

How to judge whether data misleads

  1. Look at where the vertical scale starts — a cut-off axis exaggerates differences.
  2. Check for a title and axis labels.
  3. Judge the sample: is it big enough and does it represent everyone?
  4. Read the survey question — does it lead the answer?
Example 1 — Cut-off scale
Bottles sold are \(82\) and \(88\). How big is the real difference?
Solution

Subtract the two values.

\(88-82\)\(=\)\(6\)

Small, even though the cut graph looks huge.

Example 2 — Missing labels
A graph has no title and no axis labels. Why is it poor?
Solution

A reader cannot tell what it is about or what the numbers count, so it cannot be trusted.

Example 3 — Biased sample
To find the favourite sport of \(400\) students, only \(8\) netball players are asked. What is wrong?
Solution

Far too few, and all play netball.

\(400-8\)\(=\)\(392\) not asked

The sample is biased.

Example 4 — Leading question
“Don't you agree apples are best?” Why is this a poor survey question?
Solution

It pushes the answer towards apples, so the results are not fair. Offer clear, equal choices instead.

Common pitfalls

Check where the scale starts. A cut-off axis exaggerates differences; the numbers have not changed, only the picture.
Look for a title and labels. Without them a reader cannot tell what the graph is about or what it counts.
Judge the sample. Too few people, or only one kind of person, makes a survey biased and its result unfair.

Frequently asked questions

How can a graph mislead if the numbers are right?

By how it is drawn. Cutting the scale so it starts above \(0\) makes small differences look huge, even though the values have not changed.

Why should the scale start at zero?

So heights compare fairly. When the scale is cut off, only the tops of the columns are drawn, so a small gap looks like a big one.

What makes a survey sample biased?

Asking too few people, or only one kind of person. If you ask only netball players about sport, netball is almost certain to win.

What is a leading question?

One that pushes the answer one way, like “Don't you agree apples are best?”. It makes the results unfair, so offer clear, equal choices instead.

How do I pose a fair survey question?

Make it clear, offer choices that do not overlap, and do not hint at an answer. Sampling a large, mixed group keeps the results fair.