Calculator Suite

Correlation Analysis Calculator

Correlation Analysis

Analyze relationships between variables using Pearson, Spearman, and Kendall correlation methods with comprehensive statistical testing and interactive visualizations.

Analysis Settings
Data Input Method
Analysis Settings
Ready to analyze 10 data pairs (X Variable vs Y Variable)

Educational Resources

Correlation Methods

Pearson Correlation

r=∑(xi−xˉ)(yi−yˉ)∑(xi−xˉ)2∑(yi−yˉ)2r = \frac{\sum(x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum(x_i - \bar{x})^2 \sum(y_i - \bar{y})^2}}

Measures linear relationships. Assumes normality and is sensitive to outliers.

Spearman Correlation

Based on ranked data. Captures monotonic relationships and is robust to outliers.

Kendall's Tau

Based on concordant pairs. More robust for small samples but yields smaller values.

Interpretation Guide

Correlation Strength

  • • 0.0-0.2: Very weak
  • • 0.2-0.4: Weak
  • • 0.4-0.6: Moderate
  • • 0.6-0.8: Strong
  • • 0.8-1.0: Very strong

Direction

  • • Positive: Both variables increase together
  • • Negative: One increases as other decreases
  • • Zero: No linear relationship
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