GCSE Maths • Foundation & Higher
GCSE Scatter Graphs Revision Guide
Plot paired data, describe correlation and make sensible estimates from trends.
Foundation
Exam practice
Worked examples
What You'll Learn
Plot Paired Data
Choose suitable scales, label both axes with units and plot each coordinate accurately.
Describe Correlation
Identify positive, negative or no correlation and comment on strength when appropriate.
Recognise Outliers
Spot observations that lie unusually far from the general pattern.
Draw a Best-Fit Line
Represent a roughly linear trend with a balanced straight line through the main cloud.
Make Estimates
Read from the line carefully and distinguish interpolation from extrapolation.
Evaluate Conclusions
Explain uncertainty, avoid causal claims and recognise when prediction is inappropriate.
Key Rules and Formulas
Scatter Graphs Lessons
Correlation
Identify positive, negative and no correlation, judge strength and avoid confusing association with causation.
Line Of Best Fit
Draw and use a balanced trend line for interpolation while treating extrapolation cautiously.
CORE SUBTOPICS
Axes and Scales
Use continuous numerical scales that cover all values efficiently.
Bivariate Data
Understand that each point joins two measurements from the same observation.
Non-Linear Patterns
Recognise that a curved association may exist even when a straight line is unsuitable.
Outliers
Identify unusual observations and consider their effect on interpretation.
Prediction Reliability
Use strength, range, sample context and scatter to judge an estimate.
Correlation and Causation
State that association alone cannot establish a cause-and-effect relationship.
Worked Example
Using a Line of Best Fit for an Estimate
QUESTION
A scatter graph compares revision time with test score. The plotted data cover 1 to 8 hours and show a moderately strong positive correlation. Use the drawn best-fit line to estimate the score for 6 hours.
- Given information: At x = 6, the line of best fit crosses near y = 72. Six hours lies within the observed x-range.
- Method: Read vertically from the x-value to the line, then horizontally to the y-axis, and evaluate the estimate.
- Locate 6 hours on the horizontal axis.
- Move vertically until reaching the line of best fit.
- Move horizontally to the score axis.
- Read an estimated score of about 72.
- Classify the estimate as interpolation because 6 is within the observed range 1 to 8.
- Final answer: The estimated test score is approximately 72.
- Independent answer check: The estimate lies within the main vertical range and follows the positive trend.
- One common mistake: Do not read from a nearby plotted point; the estimate must come from the best-fit line.
- Common GCSE Mistakes
- Pairing Values Incorrectly
- Leaving Axes or Units Unlabelled
- Confusing Direction and Strength
- Forcing the Line Through Every Point
- Claiming Correlation Proves Causation
- Overconfident Extrapolation
- Exam Tips
- Check axis labels, units and scales before reading or plotting.
- Describe correlation with both direction and strength when supported.
- Use tends to rather than claiming every observation follows the trend.
- Draw a ruled line through the centre of the main linear cloud.
- State whether an estimate is interpolation or extrapolation.
- Explain limitations using scatter, outliers, range and the correlation-causation distinction.
Ready to Practice?
Printable Worksheet
Download and print practice questions with answers.
Interactive Quiz
Test your knowledge with instant feedback and hints.
Exam-Style Questions
Timed questions to build confidence for the real exam.
Watch the Scatter Graphs Tutorial
Clear, step-by-step explanation of expanding brackets, simplifying complex expressions, and solving for x. Perfect for visual learners who need a breakdown of the rules in action.
- 12 minute comprehensive guide
- High-definition whiteboard walk-through
Continue Your GCSE Maths Revision
Continue Your GCSE Maths Revision
Frequently Asked Questions
One point represents a paired observation: one value for each variable from the same case.
As one variable increases, the other tends to increase, producing an upward trend.
No. Strength concerns how closely points cluster around the trend; steepness describes rate of change.
No. It should represent the observed trend and only passes through the origin if the data support that.
No. It is usually safer than extrapolation, but weak correlation, wide scatter, outliers or limited data reduce reliability.
No. Association may be explained by another variable, reverse influence or coincidence.
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