• statistical relationship where two variables change together
  • Pearson coefficient (r) ranges from -1 (perfect negative) through 0 (none) to +1 (perfect positive)
  • positive correlation: both variables increase together
  • negative correlation: one increases as the other decreases
  • does not imply causation: confounders, reverse causation, or coincidence may explain the association
  • Spearman rank correlation handles nonlinear monotonic relationships
  • spurious correlations arise from large datasets with many variables
  • partial correlation controls for the effect of a third variable
  • foundational tool in statistics, epidemiology, economics, and machine learning