Available to you free of charge, the site is designed to help you learn the concepts and terminology introduced in each chapter, and to use that knowledge to analyze real-world research. Based on real papers and experiments, these exercises involve answering questions by analyzing the data from the experiment. Instructor registration is required for student access to the quizzes. Simulation Exercises: These exercises include interactive modules that allow you to explore some of the dynamic processes of evolution. Each exercise poses questions answered by running the simulation and observing and analyzing the outcomes. Chapter Summaries: Concise overviews of the important concepts and topics covered in each chapter.
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Extensively rewritten and reorganized, this new edition of Evolution—featuring a new coauthor: Mark Kirkpatrick The University of Texas at Austin —offers additional expertise in evolutionary genetics and genomics, the fastest-developing area of evolutionary biology. Directed toward an undergraduate audience, the text emphasizes the interplay between theory and empirical tests of hypotheses, thus acquainting students with the process of science. It addresses major themes—including the history of evolution, evolutionary processes, adaptation, and evolution as an explanatory framework—at levels of biological organization ranging from genomes to ecological communities.
New to this edition Genomic perspectives on evolution are strengthened throughout The content has a stronger focus on human evolution: an entirely new chapter on the topic Chapter 21, The Evolutionary Story of Homo sapiens , and new examples throughout the book Many chapters have been rewritten from the ground up The book has been entirely reillustrated in a clean, contemporary style that enhances the content A new Appendix, A Statistics Primer, introduces the concept of a probability distribution, reviews how statistics are used to describe populations, looks at how we estimate quantities, and discusses how hypotheses are tested.
It ends with a brief overview of two major frameworks of statistical analysis: likelihood and Bayesian inference. Math is kept to a minimum. About the Author s Douglas J. Futuyma and Mark Kirkpatrick Douglas J.
He received his B. Futuyma is the author of three previous editions of Evolution, as well as three editions of its predecessor, Evolutionary Biology.
Douglas J. Futuyma - Evolution
Chapter 1 Evolutionary Biology
Douglas J. Futuyma