Chapter 9- Regression wisdom

Chapter 9- Regression wisdom

1. Outlier

   • Any data point that stands away from the others can be called an outlier. In regression, outliers can be extraordinary in two ways: by having a large residual or by having high leverage.

2. Leverage

   • Data points whose x-values are far from the mean of x are said to exert leverage on a linear model.

3. Influential point

   • If omitting a point from the data results in a very different regression model, then that point is called an influential point.

4. Lurking variable

   • A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related is called a lurking variable.

5. High leverage points

   • Pull the line close to them, and so they can have a large effect on the line, sometimes completely determining the slope and intercept. With high enough leverage, their residuals can be deceptively small.