When you are studying a response variable, you often have the opportunity to measure many predictor variables in your study. Every additional predictor variable, interaction term, power term, etc will increase R2 and thus your model will explain more of the variation in the response variable. Why, then, would we not want to include a predictor variable in our regression model? Please explain the reasoning for model simplification.

Give an example of a population with a response variable you would be interested in modeling - give examples of at least 5 predictor variables that you might consider when collecting data to create a model.