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Geometric Morphometrics for Biologists: A Primer, Third Edition explores how these geometric methods allow for the study of biological shape by incorporating the geometry of organisms throughout data analyses. Novel content on phylogenetic comparative methods, evolutionary morphology, analyses of disparity, genetics of shape, and simulating shape data is included. This edition delivers step-by-step guidance on how to effectively utilize updated analytical software while also providing guidance on important methodologies that remain relevant to the field to ensure clear and effective instruction to audiences new to this branch of data analysis.
It succeeds the second edition as the primary resource for teaching modern geometric methods of shape analysis to students, researchers, and practicing scientists in the field of organismal biology. Users will find it to be an immensely valuable introduction for students and practicing biologists interested in learning applications of multivariate statistics and matrix algebra to organismal biology.
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Geometric Morphometrics for Biologists: A Primer, Third Edition explores how these geometric methods allow for the study of biological shape by incorporating the geometry of organisms throughout data analyses. Novel content on phylogenetic comparative methods, evolutionary morphology, analyses of disparity, genetics of shape, and simulating shape data is included. This edition delivers step-by-step guidance on how to effectively utilize updated analytical software while also providing guidance on important methodologies that remain relevant to the field to ensure clear and effective instruction to audiences new to this branch of data analysis.
It succeeds the second edition as the primary resource for teaching modern geometric methods of shape analysis to students, researchers, and practicing scientists in the field of organismal biology. Users will find it to be an immensely valuable introduction for students and practicing biologists interested in learning applications of multivariate statistics and matrix algebra to organismal biology.