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Statistic measuring the strength and direction of linear association between two variables, ranging from −1 to +1.
DESCRIPTION
Pearson correlation quantifies linear association, returning a coefficient from −1 to +1. It assumes interval data, linearity, and sensitivity to outliers. The coefficient is computed as covariance normalized by standard deviations. It informs feature selection, multicollinearity checks, and exploratory analysis. Nonlinear relationships may be underestimated. Confidence intervals and significance tests assess reliability. Alternatives like Spearman rank correlation handle monotonic but non-linear associations.
ALTERNATIVE DEFINITIONS
NIST/SEMATECH e-Handbook
The Pearson correlation coefficient is a measure of the strength of the linear relationship between two variables.
Stresses linear relationship and measurement of strength.
Encyclopaedia Britannica
Correlation coefficient, a statistical measure of the strength of the relation between two variables. Pearson’s correlation coefficient (r) is the most widely used.
Positions Pearson’s r as the most common correlation measure.
Investopedia
The Pearson correlation coefficient (r) is a measure of the strength and direction of a linear relationship between two variables.
Explicitly mentions direction and linearity in accessible language.
RELATED TERMS
Covariance Linear Relationship Scatter Plot Regression Analysis p-value Hypothesis Testing Variance Feature Scaling
COMPETING TERMS
Spearman Correlation Kendall’s Tau
RELATIONS
- Broader: Correlation
KNOWLEDGE AREAS
TARGET AUDIENCE
Data Scientist Data Analyst BI Specialist
EXTERNAL SOURCES
- Wikipedia - Pearson correlation coefficient
- NIST - NIST definition and guidance
- SciPy - Pearson correlation API
- Penn State Statistics - Course material on correlation
TOP QUESTIONS
When should Pearson Correlation be used?
Use Pearson Correlation for linear relationships between continuous variables, especially when data meets assumptions of linearity and absence of significant outliers.
Category: Requirements
What is a hot topic around Pearson Correlation?
Debiasing correlation analyses in high-dimensional feature sets and using robust or rank-based alternatives when outliers or nonlinearity are present.
Category: Topic
What does the sign of Pearson Correlation indicate?
Positive indicates increasing together, negative indicates one increases as the other decreases, and magnitude shows strength.
Category: Definition
What are common mistakes with Pearson Correlation?
Assuming causation, ignoring nonlinear relationships, and not checking for outliers can mislead conclusions.
Category: Mistakes
How is Pearson Correlation computed?
It is the covariance of the variables divided by the product of their standard deviations.
Category: Definition
What are alternatives to Pearson Correlation?
Spearman rank correlation and Kendall tau measure monotonic relationships and are less sensitive to outliers.
Category: Alternatives
How to interpret Pearson Correlation magnitude?
Near ±1 suggests strong linear association; near 0 suggests weak or no linear relationship.
Category: Example
Why is Pearson Correlation still relevant?
It’s simple, widely taught, and useful for quick exploratory analysis and feature screening.
Category: Relevancy
What is the risk of relying solely on Pearson Correlation?
You may miss nonlinear patterns and be misled by confounders or spurious correlations.
Category: Risk