Correlation Coefficient Calculator

Calculate Pearson, Spearman, and Kendall correlation coefficients with statistical significance testing and comprehensive analysis

X Variable Values

Y Variable Values

Significance Level

Pearson (r): Measures linear relationships between normally distributed variables. Most commonly used.

Spearman (ρ): Non-parametric measure for monotonic relationships. Works with ordinal data and non-normal distributions.

Kendall (τ): Alternative rank-based measure, more robust to outliers and preferred for small samples.

Interpretation:

Pearson Correlation: Assumes linear relationship and normally distributed variables. Sensitive to outliers

Spearman Correlation: Non-parametric, works with any monotonic relationship. Good for ordinal data

Kendall Tau: More robust to outliers than Spearman, preferred for small samples or when ties are present

P-value: Approximate values for hypothesis testing. Lower p-values indicate stronger evidence against null hypothesis (no correlation)