Covariance |
Description | - Covariance is a statistical measure of the variability of two random variables with each other.
- Covariance between two variables hints towards a linear relationship between them.
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Why to use | To determine the relationship between two variables. |
When to use | For numerical variables | When not to use | For textual data |
Prerequisites | The data should not contain any missing values. |
Input | Numerical variable having any positive or negative value. | Output | |
Statistical Methods used | Covariance Score | Limitations | - Covariance gives the directional relationship between the variables. However, the magnitude of covariance (covariance score) is not very informative.
- The variable variance is largely affected by the presence of even a small number of outliers in the data. This may lead to misleading statistics and interpretations.
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Covariance indicates a relationship between two variables when there is a change in their values. In case of positive covariance, an increase in one variable increases the other variable. Thus, both the variables move in the same direction. The positive covariance is denoted by a positive number.
When there is a negative covariance, an increase in one variable decreases the other variable. Thus, both the variables move in opposite directions. The negative covariance is denoted by a negative number.
The values of covariance between two random variables can lie between positive infinity and negative infinity (+∞ to -∞) limits.