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Concept

Association

The association of bivariate data means the relationship between two variables in a data set. Analyzing bivariate data involves considering how changes in one variable relate to changes in another. The relationship can exhibit a positive linear, negative linear, non-linear association, or exhibit no association.

Identifying the association in bivariate data leads to recognizing patterns, making predictions, and drawing conclusions about the relationship between the two data sets.

Extra

Similarities and Differences Between Association and Correlation

The table outlines the similarities and differences between association and correlation.

Similarities	Differences
Both describe the relationship between two random variables. Both use scatter plots for analyzing relationships between variables.	Correlation detects linear relationships; association detects both linear and non-linear relationships. Correlation quantifies a relationship with a number between - 1 and 1; association does not quantify.

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