Correlation coefficient
Pearson’s correlation coefficient measures the direction and strength of a linear association between two variables on a scale from−1 to+1. A value near+1 indicates a strong positive linear pattern and near−1 a strong negative pattern; a value near0 indicates little linear association. It does not measure the slope, prove causation or rule out a curved relationship. Its interpretation can be sensitive to unusual observations and the range of the data.
Worked example
A coefficient of−0.9 suggests a strong negative linear association: higher values of one variable tend to accompany lower values of the other. It does not mean that a1% increase necessarily causes a0.9% decrease.
Common mistake
Reading the coefficient as a percentage change or taking a negative coefficient to mean a weak relationship.
Where it appears in your exams
| Qualification | Exam | Relationship | Period |
|---|---|---|---|
| ACCA | MA | Direct | September 2026–June 2027 |
| FIA | FMA | Direct | September 2026–June 2027 |