Strong positive
- Input
- horas de estudo × nota no exame
- Expected output
- r ≈ 0.85
72% of the grade variance is explained by study hours.
how to interpret Pearson correlation
How to Interpret the Pearson Correlation
r near ±1 indicates strong linear correlation. r near 0 indicates weak correlation. r² measures the proportion of Y's variance explained by X.
Continue in the tool
Open full toolScale for interpreting r
- Common classification: |r| ≥ 0.9 (very strong), 0.7–0.9 (strong), 0.5–0.7 (moderate), 0.3–0.5 (weak), < 0.3 (negligible). Thresholds vary by field.
- r = 0.7 → r² = 0.49 (49% of Y's variance explained by X). r = 0.3 → r² = 0.09 (only 9%). The jump in r² is non-linear.
Examples
Spurious correlation
- Input
- consumo de sorvete × afogamentos
- Expected output
- r ≈ 0.95
High correlation but spurious causation — both rise in summer.
Full tool FAQ
Pearson's r measures the strength and direction of the linear relationship between two variables. It ranges from −1 to +1: values near ±1 indicate strong correlation; near 0 indicate weak or absent correlation.
Frequently asked questions
Does r = 0 mean statistical independence?
Not necessarily. r = 0 indicates no LINEAR correlation. A perfect curvilinear relationship can exist with r = 0 (e.g. y = x²).
Does this page replace official or professional review?
No. It helps explain the scenario and use the tool more safely, but real decisions should consider official sources, full context and qualified guidance when needed.