Today we focused on some issues that arise when there is more than one explanatory variable in a regression model (i.e., multiple regression). This included the interpretation of the partial slopes/effects and the importance in some cases of controlling for the effects of other variables, and collinearity — what it is and why it can be a problem. I also introduced the concept of influence and leverage — that the influence of an observation depends on its leverage and residual.
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