Correlation (Extended)
Understand Pearson's correlation coefficient, interpret r values and distinguish causation from correlation. IB MYP Year 5 Extended Maths statistics guide.
From Description to Measurement
While Standard level students describe correlation qualitatively, Extended students work with a numerical measure: Pearson's correlation coefficient (r). This gives a precise value for the strength and direction of a linear relationship between two variables.
Pearson's Correlation Coefficient
The value of r always lies between −1 and 1:
- r = 1: Perfect positive linear correlation
- r = −1: Perfect negative linear correlation
- r = 0: No linear correlation
- 0.7 ≤ |r| < 1: Strong correlation
- 0.3 ≤ |r| < 0.7: Moderate correlation
- |r| < 0.3: Weak correlation
In MYP assessments, r is typically provided or calculated using a GDC. You are expected to interpret the value, not derive the formula from scratch.
Interpreting r in Context
Simply stating "r = 0.85, which is strong positive correlation" is insufficient at Extended level. A complete response should:
- State the value of r
- Describe the strength and direction
- Interpret what this means for the specific variables in the question
Causation vs Correlation
A strong correlation does not imply that one variable causes the other. This is one of the most important conceptual distinctions in statistics. MYP questions regularly test whether students can identify confounding variables or explain why correlation is not sufficient evidence of causation.
Example: Ice cream sales and drowning rates are positively correlated, but both are driven by a third variable — hot weather.
Common Mistakes
- Concluding causation from a high r value
- Applying r to non-linear relationships
- Describing correlation direction incorrectly when r is close to zero