Differences Between Covariance and Correlation
Aspect | Covariance | Correlation |
---|---|---|
Calculation | Calculates the average of the product of deviations from means | Standardizes covariance by dividing by the product of standard deviations |
Interpretation | Positive: Variables move together. Negative: Variables move inversely. Zero: No linear relationship | Perfect Positive (1): Variables move in perfect positive correlation. Perfect Negative (-1): Variables move in perfect negative correlation. No correlation (0): No linear relationship. |
Unit Dependency | Sensitive to changes in variable scales. Units of measurement directly influence magnitude. | Unitless measure: Not affected by variable scales or units of measurement. |
Magnitude of Relationship | Provides information on direction and variability of variables. | Quantifies strength and direction of linear relationship. |
When to Use | Directional relationship analysis. Variability assessment. Dimensionality reduction. | Standardized relationship analysis across datasets. Multivariate analysis. Risk assessment. |
Inference | Covariance alone is not sufficient for statistical inference. | Used in statistical tests such as t-tests, ANOVA, etc., for inference. |
Covariance vs Correlation: Understanding Differences and Applications
Understanding the relation between variables is seen as an essential component of Machine Learning. With covariance and correlation serving as two key concepts for quantifying this relationship. Despite being often used interchangeably, covariance and correlation have unique meanings and uses.
In this guide, we will understand the concepts of Covariance and Correlation, their differences, advantages, disadvantages, and real-world applications.
Table of Content
- Understanding Covariance and Correlation
- Differences Between Covariance and Correlation
- Covariance vs Correlation : Exploring the Formula and Their Calculations
- Covariance and Correlation: Understanding the Differences and Interpretation
- Unit Dependency Between Covariance and Correlation
- Choosing Between Covariance and Correlation: When to Use Each
- Advantages and Disadvantages of Covariance
- Advantages and Disadvantages of Correlation
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