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Mathematical Models in the Health Sciences was first published in 1979.This book, designed especially for use in graduate courses in the health sciences, will be useful also as a reference work for scientists in various disciplines. It provides an introduction to mathematical modeling through the use of selected examples from the health sciences. Where appropriate, computer techniques are discussed and illustrated with examples drawn from studies by the authors and their colleagues. An introductory chapter discusses mathematical models and their roles in biomedical research. The rest of the material is divided in three sections of four chapters each: Deterministic Models, Time Series Analysis, and Information and Simulation. A bibliography accompanies each chapter. In their conclusion the authors place mathematical biology and its techniques in perspective.

Over the last several decades, mathematical models have become central to the study of social evolution, both in biology and the social sciences. But students in these disciplines often seriously lack the tools to understand them. A primer on behavioral modeling that includes both mathematics and evolutionary theory, Mathematical Models of Social Evolution aims to make the student and professional researcher in biology and the social sciences fully conversant in the language of the field.

Teaching biological concepts from which models can be developed, Richard McElreath and Robert Boyd introduce readers to many of the typical mathematical tools that are used to analyze evolutionary models and end each chapter with a set of problems that draw upon these techniques. Mathematical Models of Social Evolution equips behaviorists and evolutionary biologists with the mathematical knowledge to truly understand the models on which their research depends. Ultimately, McElreath and Boyd’s goal is to impart the fundamental concepts that underlie modern biological understandings of the evolution of behavior so that readers will be able to more fully appreciate journal articles and scientific literature, and start building models of their own.