Correlation
A statistical measure that expresses the extent to which two variables fluctuate together.
What is Correlation?
Correlation quantifies the direction and strength of the linear relationship between two continuous variables. The most common metric is Pearson's correlation coefficient (r), which ranges from -1 (perfect negative correlation) to +1 (perfect positive correlation), with 0 indicating no linear relationship.
Why Correlation Matters
It allows researchers to identify predictive relationships and underlying patterns between variables in observational data.
How to Interpret
An r value of 0.8 indicates a strong positive relationship, while an r of -0.2 indicates a weak negative relationship. The statistical significance of the correlation depends on the sample size.
Example
There is a positive correlation between hours studied and exam scores: as study time increases, exam scores tend to increase. There is a negative correlation between altitude and temperature.
Common Mistakes
- Assuming correlation implies causation (e.g., ice cream sales correlate with drowning deaths, but heat causes both).
- Using Pearson correlation for non-linear relationships (where a U-shaped relationship might yield an r of 0, missing the pattern entirely).