How to Use This Guide Hub
This page exists to help readers choose the right learning path before they start calculating. Search engines often send visitors to an overview page first, so this hub is designed to answer the immediate "where should I go next?" question instead of acting as a thin list of links.
Start with the foundation
Read the full correlation guide if you want definitions, interpretation rules, and a clear explanation of how the major coefficients differ.
- Best for first-time learners
- Covers direction, strength, and uncertainty
- Explains why correlation does not imply causation
Compare methods before you calculate
Use the method summaries below when you already know your dataset but need to choose the correct statistic quickly.
- Pearson for linear numeric relationships
- Spearman for ranked or monotonic data
- Kendall for smaller tie-heavy samples
- Point-biserial for binary versus continuous data
Practice with worked datasets
Move into examples once you understand the basics. Comparing the same data across methods is one of the fastest ways to build intuition.
- See when coefficients agree
- See when method choice changes interpretation
- Use the calculators with concrete sample data