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Chapter 11: Multiple Regression

Chapter 11: Multiple Regression

pp. 210-242

Authors

, University of Birmingham, , Norwegian School of Economics and Business Administration, Bergen-Sandviken, , University of Sussex
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Summary

The most commonly used technique for the analysis of quantitative data in business research is multiple regression analysis. This is a powerful technique for understanding the relationships between variables, which variables have the most impact, and for prediction. In this chapter, we consider how to specify regression models, how to estimate the models, and how to use the estimated models to undertake some simple hypothesis tests. We emphasize that the researcher has to exercise his/her judgement in deciding not only the specification of the initial model but also in how to adapt and interpret the model in response to the various statistical tests.

Keywords

  • multiple regression
  • variable operationalization
  • functional form
  • time lags
  • OLS estimation
  • estimation problems
  • residual plot
  • hypothesis testing

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