Both correlation and regression work with quantitative or qualitative data.
Correlation is a single statistic or data point, whereas regression is the entire equation where every data point is represented by a line. Correlation shows the relationship between two variables, and regression lets you see how one affects the other.
The most commonly used techniques for examining the relationship between two quantitative variables are correlation and linear regression. Correlation quantifies the strength of the linear relationship between pairs of variables, and regression expresses the relationship in equation form.
Correlation and regression coefficients are used to analyze relationships between variables. These coefficients are calculated using quantitative or qualitative variables.
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