Abstract
Models are used to accomplish two complementary goals: identification of key drivers of performance and prediction of performance under alternative scenarios. The variables selected affect both the explanatory accuracy and power of models, as well as forecasting precision. In this chapter, the focus is on variable selection, the first step in the process used to build powerful and accurate multiple regression models.
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© 2013 Springer Science+Business Media New York
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Fraser, C. (2013). Building Multiple Regression Models. In: Business Statistics for Competitive Advantage with Excel 2013. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7381-7_10
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DOI: https://doi.org/10.1007/978-1-4614-7381-7_10
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Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-7380-0
Online ISBN: 978-1-4614-7381-7
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