Correlation and regression are two related yet distinct concepts in statistics. Correlation is used to measure the strength of a relationship between two variables, while regression is used to make predictions about one variable based on another. Both can be helpful for understanding data sets.
About Difference Between Correlation And Regression
| Correlation | Regression |
|---|---|
| Measures the strength of a relationship between two variables | Analyzes the relationship to make predictions about one variable based on another |
| Determines if a linear relationship exists | Evaluates the strength and direction of that linear relationship |
| Describes the degree to which two variables are related | Estimates the value of one variable when the other is known |
| No assumptions about the distribution of data | Assumes that there is a linear relationship between the variables |
| Does not involve prediction | Involves prediction of one variable from another |
| Results in correlation coefficient | Produces an equation for a line that best fits the data |
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