The Regression Line

In the regression line equation the constant $m$ is the slope of the line and $b$ is the $y$-intercept.

ANCOVA can be used to compare regression lines by testing the effect of a categorial value on a dependent variable, controlling the continuous covariate.

The criteria for determining the least squares regression line is that the sum of the squared errors is made as small as possible.

Standard linear regression models with standard estimation techniques make a number of assumptions.

The slope of the best fit line tells us how the dependent variable $y$ changes for every one unit increase in the independent variable $x$, on average.

Regression toward the mean says that if a variable is extreme on its 1st measurement, it will tend to be closer to the average on its 2nd.