Abstract
Models are abstract, simplified representations of reality, often used both in science and in technology. No one should believe that a model could be true, although much of theoretical statistical inference is based on just this assumption. Models may be deterministic or probabilistic. In the former case, outcomes are precisely defined, whereas, in the latter, they involve variability due to unknown random factors. Models with a probabilistic component are called statistical models.
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© 1997 Springer-Verlag New York, Inc.
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(1997). Generalized Linear Modelling. In: Applying Generalized Linear Models. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-22730-6_1
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DOI: https://doi.org/10.1007/978-0-387-22730-6_1
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-98218-2
Online ISBN: 978-0-387-22730-6
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