Calculate correlation coefficient (Pearson r and Spearman ρ) between two datasets. Find the strength and direction of relationships with R², scatter plots, regression lines, and step-by-step calculations.
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Calculate correlation coefficients to measure the relationship between two variables. Compute Pearson r for linear relationships, Spearman ρ for monotonic relationships, and coefficient of determination (R²). Includes interactive scatter plots with regression lines and detailed statistical analysis.
The correlation coefficient is a statistical measure that describes the strength and direction of a linear relationship between two variables. It ranges from -1 to +1, where +1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 indicates no linear relationship. Pearson's r measures linear correlation, while Spearman's ρ measures monotonic relationships and is more robust to outliers.
Pearson Correlation Formula
r = Σ(xᵢ - x̄)(yᵢ - ȳ) / √[Σ(xᵢ - x̄)² × Σ(yᵢ - ȳ)²]Measure relationships between variables in experiments, from drug dosage effects to environmental factors.
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Use Pearson (r) when your data is continuous, normally distributed, and you expect a linear relationship. Use Spearman (ρ) when data is ordinal, has outliers, is non-normal, or when you're testing for any monotonic relationship (not just linear). Spearman is also better for ranked data or when relationships are curved but consistently increasing or decreasing.