Abstract
The contemporary biological data from which so many inferences are made are the result of evolution, that is, of an indescribably complicated stochastic process. Very simplified models of this process are often used in the literature, in particular for the construction of phylogenetic trees, and aspects of these simplified models are discussed in this chapter. The emphasis is on introductory statistical and probabilistic aspects. A probabilistic approach has the merit of allowing the testing of various hypotheses concerning the evolutionary process. Hypothesis-testing questions in the evolutionary context are discussed in Section 14.9.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer Science+Business Media New York
About this chapter
Cite this chapter
Ewens, W.J., Grant, G.R. (2001). Evolutionary Models. In: Statistical Methods in Bioinformatics. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-3247-4_13
Download citation
DOI: https://doi.org/10.1007/978-1-4757-3247-4_13
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4757-3249-8
Online ISBN: 978-1-4757-3247-4
eBook Packages: Springer Book Archive