1. Chapter 9
Regression Wisdom

2. Residuals
Residuals are what is left over after the model describes the relationship
Must use the residuals to check if the linear model is reasonable

3. Linear Models Provide a predicted value
The farther the new X value is from the Xbar
Regression equation is the same as the linear model

4. Leverage Linear model does not work very well with large residuals
A data point can be unusual if its x-value is far from the mean of such x-values.
All lines pass through xbar and ybar

5. Influential
If omitting it from the analysis gives a very different model
Depends on the leverage and the residual
Take a value out and redo the regression

6. Lurking Variable
Not part of a model but affects ways that the models appear
We can never be certain of a lurking variable
That is way you can never use “causal”.