A LITTLE PRACTICE, EVERY DAY·GCSE MATHS
AQA·Edexcel·OCR|Foundation + Higher
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Statistics & Probability · Foundation & Higher

Scatter graphs & correlation

Scatter graphs plot two variables to see if there is a relationship (correlation) between them. You need to describe the type and strength of correlation and draw lines of best fit.

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Revising scatter graphs & correlation the night before an exam? These are condensed revision notes — the facts, formulas and mistakes examiners actually mark, with no long explanations. Prefer a full walkthrough with step-by-step reasoning instead? Search “Scatter graphs & correlation GCSE” on the site for the complete guide.

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Key facts to remember

  • 1Positive correlation: as one variable increases, the other increases.
  • 2Negative correlation: as one variable increases, the other decreases.
  • 3No correlation: no clear pattern between the variables.
  • 4Correlation can be strong (points close to a line) or weak (points scattered widely).
  • 5Correlation does not imply causation — two things may be related without one causing the other.
  • 6An outlier is a point that does not fit the general pattern.
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Worked examples

Example 1

A scatter graph of temperature vs ice cream sales shows points rising from bottom-left to top-right. Describe the correlation.

Working

  1. As temperature increases, ice cream sales increase
  2. Points rise from bottom-left to top-right → positive correlation
  3. Points are close together → strong positive correlation
AnswerStrong positive correlation
Example 2

A scatter graph shows hours of revision vs exam errors. Describe the expected correlation.

Working

  1. More revision → fewer errors
  2. One increases while the other decreases → negative correlation
AnswerNegative correlation
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Common mistakes

✗Confusing positive and negative correlation — positive means both go up together.
✗Stating that a correlation proves one variable causes the other.
✗Joining plotted points with a line instead of drawing a line of best fit.
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Exam tips

✓Use precise language: "strong positive correlation" not just "positive".
✓Correlation describes the relationship, not causation — avoid saying one variable "causes" the other.

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