Abstract
If the relationship between a response variable Y and an explanatory variable X is believed to be nonlinear, it is sometimes possible to model the relationship by adding an X 2-term to the model in addition to an X-term. For example, if Y is product demand and X is advertising expenditure on the product, an analyst might feel that beyond some value of X, there is “diminishing marginal returns” on this expenditure. Then the analyst would model Y as a function of X and X 2, and possibly other predictor variables, and anticipate a significant negative coefficient for X 2. Occasionally a need is encountered for higher-order polynomial terms.
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© 2009 Springer Science+Business Media, LLC
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Heiberger, R.M., Neuwirth, E. (2009). Polynomial Regression. In: R Through Excel. Use R. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0052-4_11
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DOI: https://doi.org/10.1007/978-1-4419-0052-4_11
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Online ISBN: 978-1-4419-0052-4
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