Statistics in Action Case: Automated Modeling
Good regression modeling starts with familiarity with the substance of the problem and a thorough understanding of the response and explanatory variables. When the data include many possible explanatory variables, it can take hours of careful analysis to arrive at a model. Even then, we are seldom sure that we’ve made complete use of the explanatory variables. The need for an immediate answer often requires that we resort to an automated search for the explanatory variables that accurately predict the response. ...
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