Multiple Regression Analysis

  • Venkat Reddy Konasani
  • Shailendra Kadre
Chapter

Abstract

In Chapter 9, we discussed correlation, which is used for quantifying the relation between a pair of variables. We also discussed simple regression, which helps predict the dependent variable when an independent variable is given. In simple regression, you use a single independent variable to predict the dependent variable. This is a simplistic approach, and in practice some dependent variables may require more than one independent variable for accurate predictions. For example, can you predict the gross domestic product (GDP) of a nation by looking just at exports? The obvious answer is that it can’t be done. Predicting the GDP may need several other variables, such as per-capita income, value of natural resources, national debt, and so on. Likewise, the health of an individual depends upon many variables, such as smoking or drinking habits, eating habits, job pressure, daily workouts, genetics, sleeping habits, and more.

Keywords

Gross Domestic Product Stock Market Variance Inflation Factor Beta Coefficient Stock Market Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Venkat Reddy Konasani 2015

Authors and Affiliations

  • Venkat Reddy Konasani
    • 1
  • Shailendra Kadre
    • 1
  1. 1.APIndia

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