# Summary

Let's wrap up this chapter.

Linear model analysis with continuous explanatory variables is known as linear regression. Linear regression models the relationship between response and explanatory variables using straight lines. These lines are defined by a regression intercept and slope. The regression intercept is the value of $y$ when $x=0$. Linear regression models assume that the unexplained variability around the line is approximately normal with constant variance.

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