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Types of Correlation Examples

Part of Scatter Graphs — GCSE Mathematics

This diagram covers Types of Correlation Examples within Scatter Graphs for GCSE Mathematics. Revise Scatter Graphs in Statistics for GCSE Mathematics with 14 exam-style questions and 20 flashcards. This topic appears less often, but it can still be a useful differentiator on mixed-topic papers. It is section 4 of 7 in this topic. Focus on the labels, the relationships between parts, and the explanation that turns the diagram into an exam-ready answer.

Topic position

Section 4 of 7

Practice

14 questions

Recall

20 flashcards

Types of Correlation Examples

Strong Positive Weak Positive No Correlation Weak Negative Strong Negative Example: Study Time vs Test Score 0 2 4 6 8 10 Study Time (hours) 0 20 40 60 80 100 Test Score (%) Outlier Line of best fit Strong Positive Correlation

Keep building this topic

Read this section alongside the surrounding pages in Scatter Graphs. That gives you the full topic sequence instead of a single isolated revision point.

Understanding CorrelationDrawing Lines of Best FitDiscovering Relationships in DataKey Facts About Scatter Graphs

Practice Questions for Scatter Graphs

A scatter graph shows that as temperature increases, ice cream sales also increase. This is an example of:

  • A. Negative correlation
  • B. Positive correlation
  • C. No correlation
  • D. Causation
1 markfoundation

A scatter graph shows a strong positive correlation between the number of ice creams sold and the number of drowning incidents at a beach. A student says: 'Ice cream causes drowning.' Explain why this conclusion is incorrect.

2 marksstandard

Quick Recall Flashcards

What is no correlation?
No correlation (or zero correlation) occurs when there's no clear relationship between the variables. Points on the scatter graph appear randomly scattered with no obvious pattern.
What is correlation?
Correlation describes the relationship between two variables. It shows how one variable changes when the other variable changes, but doesn't necessarily mean one causes the other.

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Understanding Correlation

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Drawing Lines of Best Fit