Abstract
This chapter revises the basic concepts of linear regression, shows how to apply linear regression in R, discusses model validation, and outlines the limitations of linear regression when applied to ecological data. Later chapters present methods to overcome some of these limitations; but as always before doing any complicated statistical analyses, we begin with a detailed data exploration. The key concepts to consider at this stage are outliers, collinearity, and the type of relationships between the variables. Failure to apply this initial data exploration may result in an inappropriate analysis forcing you to reanalyse your data and rewrite your paper, thesis, or report.
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© 2009 Springer Science+Business Media, LLC
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Zuur, A.F., Ieno, E.N., Walker, N.J., Saveliev, A.A., Smith, G.M. (2009). Limitations of Linear Regression Applied on Ecological Data. In: Mixed effects models and extensions in ecology with R. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/978-0-387-87458-6_2
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DOI: https://doi.org/10.1007/978-0-387-87458-6_2
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Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-87457-9
Online ISBN: 978-0-387-87458-6
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