# Linear regression

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The first step to understanding **linear regression** is to make sure you understand linear correlation.

Regression examines the relationship between two variables by determining the line of best fit (on a scatterplot). The properties of this line of best fit are determined as the slope (b) and where it touches the Y-axis (a).

Regression involves:

- A predictor (X) variable, or an independent variable (IV), shown on the X-axis
- An outcome (Y) variables, or a dependent variable (DV), shown on the Y-axis

The generic equation for a simple linear regression is:

## See also[edit | edit source]

- Linear regression (Wikipedia)
- Multiple linear regression