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3.4a · Critical Analysis of Data & Models · Sub-skill

Misleading Graphs

Spotting the tricks used to make graphs tell a misleading story — truncated axes, inconsistent scales, and cherry-picked data.

Build it up, step by step

Understanding misleading graphs

Click each step below to reveal it — work through them in order the first time round.

Step 1 · Truncated (broken) axes

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A truncated axis doesn't start at zero. This can make small differences look dramatic — a bar chart where the y-axis starts at 90 instead of 0 makes a change from 92 to 96 look huge, even though it's really only about a 4% increase.

Step 2 · Inconsistent or misleading scales

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Watch for axes where the intervals aren't equal (e.g. jumping 0, 10, 50, 100), or two different scales used on the same graph without being made clear. Pictograms are especially prone to this: scaling an image up in both height and width to represent a bigger number exaggerates the size difference, since area grows faster than the actual value.

Step 3 · Selective data / cherry-picking

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A graph might only show a short time period, or specific categories, chosen specifically because they support a particular narrative, while excluding data that would tell a different story. Always ask: what date range/categories are shown, and what's been left out?

Step 4 · Reading and critiquing graphs critically

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Systematically check: does the axis start at zero? Are the scale intervals equal? Is the labelling clear and not misleading? Is any data missing or selectively shown? State clearly and specifically what is misleading and why, rather than just saying ‘the graph is wrong.’

Worked example

A company's bar chart shows sales rising from £48,000 to £52,000 over two years, with the y-axis running from £45,000 to £52,000. Explain why this graph could be considered misleading.

Because the y-axis is truncated (doesn't start at £0), the visual height of the second bar appears roughly 4 times taller than the first, even though sales only increased by about 8.3% (from 48,000 to 52,000). This exaggerates the apparent growth to someone glancing at the chart.

Test yourself

Past-paper style question

A politician presents a line graph showing crime rates ‘falling dramatically’ over the last 2 years, but the y-axis only runs from 40 to 45 (crimes per 1000 people), and the x-axis only covers the most recent 2 years, even though data is available going back 10 years.

(a) Explain two ways this graph could be considered misleading.
(b) Suggest one change that would make the graph a fairer representation of the data. [4 marks]

Show the answer

(a) First, the y-axis is truncated (starts at 40, not 0), which exaggerates the visual size of any fall in crime rate, making a small change look dramatic. Second, only showing the most recent 2 years (when 10 years of data exists) could be cherry-picking a period that particularly suits the argument being made, hiding a longer-term trend that might tell a different story.

(b) Extending the y-axis to start at 0, and/or showing all 10 years of available data, would give a fairer, more complete picture of the actual trend.

Practice

Misleading Graphs worksheet

Five short questions on misleading graphs. Work through them, then reveal the mark scheme to check.

  1. Explain what is meant by a ‘truncated axis’ on a bar chart.
  2. A pictogram uses larger images (scaled in both height and width) to represent bigger values. Explain why this can be misleading.
  3. A company shows only its best-performing quarter's sales figures in a report, without mentioning the other three quarters. Explain why this could give a misleading impression.
  4. Explain how a graph with a truncated y-axis could make a 2% increase look like a 50% increase.
  5. Give one question you should always ask yourself when looking critically at any graph presented in the media.

Mark scheme

  1. A truncated axis is one that doesn't start at zero (it's been ‘cut off’ or starts partway up the scale), which can exaggerate the apparent size of differences between values.
  2. Scaling an image in both height and width to represent a bigger number increases its area by more than the actual increase in value (area grows with the square of the scale factor), making the difference look much bigger than it really is.
  3. Showing only the best-performing quarter cherry-picks data that supports a positive narrative, while hiding weaker results from other quarters — giving a misleadingly rosy overall impression of the company's performance.
  4. If the y-axis is truncated to only show a narrow range near the two data points (e.g. 98 to 100), even a genuinely small 2% increase could visually fill almost the entire height of the chart, making it look dramatic, even though the true percentage change is small.
  5. Any sensible critical question, e.g.: ‘Does the axis start at zero?’, ‘What time period or categories are shown, and what might be missing?’, ‘Are the scale intervals equal?’
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