Correlation and association

Correlation analysis explores the association between two or more variables and makes inferences about the strength of the relationship.

Note: It is common to use the terms correlation and association interchangeably. Technically, association refers to any relationship between two variables, whereas correlation is often used to refer only to a linear relationship between two variables. The terms are used interchangeably in this guide, as is common in most statistics texts.

Scatter plot
A scatter plot shows the association between two variables. A scatter plot matrix shows all pairwise scatter plots for many variables.
Covariance
Covariance is a measure of how much two variables change together. A covariance matrix measures the covariance between many pairs of variables.
Correlation coefficient
A correlation coefficient measures the association between two variables. A correlation matrix measures the correlation between many pairs of variables.
Inferences about association
Inferences about the strength of association between variables are made using a random bivariate sample of data drawn from the population of interest.

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