AQA · A-Level · Psychology
Course version: 7182-2025 · Exams from 2027
Use a scatter diagram to identify a correlation between two variables (to…
Full specification wording
Handling data: Use a scatter diagram to identify a correlation between two variables (to include: plotting two variables from an investigation on a scatter diagram and identifying the pattern as a positive correlation, a negative correlation or no correlation)
A scattergram displays the relationship between two continuous co-variables, not a difference between conditions.
Checked against the AQA 7182-2025 specification (opens in a new tab) on .
- Point 8 of 17
- 3 key terms
Study notes
From the checked teaching notes for this specification point.
The idea
A scattergram displays the relationship between two continuous co-variables, not a difference between conditions. To plot one, place one operationalised co-variable on each axis, label both with units, and mark one point per participant where their two scores intersect. The pattern reveals the correlation: points sloping upwards from bottom-left to top-right indicate a positive correlation (both variables increase together); a downward slope indicates a negative correlation (one increases as the other decreases); a random scatter shows no correlation. At A-level, this pattern is quantified by a correlation coefficient from -1.0 to +1.0. The sign indicates direction, while the distance from zero indicates strength. Crucially, a strong correlation never establishes causation, as an untested third variable may be responsible.
What earns the marks
- Construction: both axes must be labelled with the operationalised co-variable and its unit, using a sensible scale, with a single point per participant where their scores intersect.
- Identifying patterns: a positive correlation occurs when both co-variables rise together; a negative correlation when one rises as the other falls; zero correlation when there is no consistent pattern.
- Correlation coefficients: a value near +1.0 or -1.0 indicates a strong relationship, while a value near 0 indicates a weak or absent one; the sign denotes direction, not strength (e.g., -0.85 is stronger than +0.60).
- Curvilinear relationships: scattergrams can reveal non-linear relationships (e.g., the Yerkes-Dodson law) which produce a coefficient near zero despite a predictable pattern.
- Causation fallacy: a relationship between two co-variables cannot prove causation, as the direction of effect is unknown and an untested third variable (confounding variable) may be responsible.
Common mistakes and how to put them right
Labelling the axes as 'independent variable' and 'dependent variable', which incorrectly implies an experimental design rather than a correlational analysis of co-variables.
Interpreting a steep downward pattern (negative correlation) as a weak or absent relationship, confusing the negative sign with a lack of strength.
Concluding that one co-variable causes changes in the other, failing to acknowledge the third variable problem and losing evaluation marks.
Exam tips
- When plotting a scattergram, ensure you provide a clear title naming both co-variables and accurately plot each participant's pair of scores to secure full construction marks.
- If asked what a scattergram suggests about a hypothesis, explicitly state the direction of the relationship using the specific variables named in the stem, then comment on its strength.
Try the lesson
The start of the Handling data: Use a scatter diagram to identify a correlation between two variables (to include: plotting two variables from an investigation on a scatter diagram and identifying the pattern as a positive correlation, a negative correlation or no correlation) lesson, made from checked teaching notes for this specification point.
Have a go first
A psychologist plots a scatter diagram to investigate the relationship between the number of hours students spend revising and their final exam scores. The points on the scatter diagram form a pattern that goes from the bottom left to the top right of the graph. What type of correlation does this pattern indicate?
Listen
A scattergram displays the relationship between two continuous co-variables, not a difference between conditions. To plot one, place one operationalised co-variable on each axis, label both with units, and mark one point per participant where their two scores intersect. The pattern reveals the correlation: points sloping upwards from bottom-left to top-right indicate a positive correlation (both variables increase together); a downward slope indicates a negative correlation (one increases as the other decreases); a random scatter shows no correlation. At A-level, this pattern is quantified by a correlation coefficient from -1.0 to +1.0. The sign indicates direction, while the distance from zero indicates strength. Crucially, a strong correlation never establishes causation, as an untested third variable may be responsible. A strong answer earns marks for these points. Construction: both axes must be labelled with the operationalised co-variable and its unit, using a sensible scale, with a single point per participant where their scores intersect. Identifying patterns: a positive correlation occurs when both co-variables rise together; a negative correlation when one rises as the other falls; zero correlation when there is no consistent pattern. Correlation coefficients: a value near +1.0 or -1.0 indicates a strong relationship, while a value near 0 indicates a weak or absent one; the sign denotes direction, not strength (e.g., -0.85 is stronger than +0.60). Curvilinear relationships: scattergrams can reveal non-linear relationships (e.g., the Yerkes-Dodson law) which produce a coefficient near zero despite a predictable pattern. Exam tip: When plotting a scattergram, ensure you provide a clear title naming both co-variables and accurately plot each participant's pair of scores to secure full construction marks.
Key words
Say what each word means before you turn the card.
co-variables
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correlation coefficients
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causation and third variables
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See every definition
- co-variables
- Two continuous variables plotted on a scattergram to display the relationship between them, rather than a difference between conditions.
- correlation coefficients
- A value from -1.0 to +1.0 that quantifies the pattern on a scattergram, where the sign indicates direction and the distance from zero indicates strength.
- causation and third variables
- A relationship between two co-variables cannot prove causation, as the direction of effect is unknown and an untested third variable may be responsible.
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