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MULTIPLE REGRESSION BASICS

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MULTIPLE REGRESSION BASICS . MULTIPLE REGRESSION BASICS . Documents prepared for use in course , New York University, Stern School of Business Introductory thoughts about MULTIPLE REGRESSION page 3. Why do we do a MULTIPLE REGRESSION ? What do we expect to learn from it? What is the MULTIPLE REGRESSION model? How can we sort out all the notation? Scaling and transforming variables page 9. Some variables cannot be used in their original forms. The most common strategy is taking logarithms, but sometimes ratios are used. The gross size concept is noted. Data cleaning page 11. Here are some strategies for checking a data set for coding errors. Interpretation of coefficients in MULTIPLE REGRESSION page 13.

Indicator variables page 20 Special techniques are needed in dealing with non-ordinal categorical independent variables with three or more values. A few comments relate to model selection, the topic of another document. Noise in a regression page 32 Random noise obscures the exact relationship between the dependent and

  Indicator, Variable, Indicator variables

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