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Course in Mathematical Modeling - 99 edition

Course in Mathematical Modeling (ISBN10: 088385712X; ISBN13: 9780883857120)
ISBN13: 978-0883857120
ISBN10: 088385712X

Summary: The emphasis of this book lies on the teaching of mathematical modeling rather than simply presenting models. To this end the book starts with the simple discrete exponential growth model as a building block, and successively refines it. This involves adding variable growth rates, multiple variables, fitting growth rates to data, including random elements, testing exactness of fit, using computer simulations and moving to a continuous setting. No advanced knowledge i mores assumed of the reader, making this book suitable for elementary modeling courses. The book can also be used to supplement courses in linear algebra, differential equations, probability theory and statistics. less

Edition/Copyright: 99
Cover: Paperback
Publisher: Mathematical Association of America
Published: 03/01/1999
International: No

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Brand new. We distribute directly for the publisher. A Course in Mathematical Modeling is intended as a text for a modeling course accessible to students who have mastered a one year course in calcul moreus. Mooney and Swift's approach to modeling is presented balancing theoretical versus empirical models, analytic models versus simulation, deterministic versus stochastic models, and discrete versus continuous models. Most examples are drawn from real world data or from models that have been used in various applied fields. The use of computers in both simulation and analysis is an integral part of the presentation.The authors emphasize teaching modeling as opposed to presenting models, beginning their book with the simple discrete exponential growth model as a building block, and successively refining it. This refinement includes adding variable growth rates and multiple variables, fitting growth rates to data, including random elements, testing goodness of fit, using computer simulations, and moving to a continuous setting.Students taking a course based on this book should have some mathematical maturity, but will need little advanced knowledge. The book presents more advanced topics on an as needed basis and serves to show how the different topics of undergraduate mathematics can be used together to solve problems. This perspective is valuable as either a road map for the beginning student or as a capstone for the more advanced students. The course presents elements of discrete dynamical systems, basic probability theory, differential equations, matrix algebra, stochastic processes, curve fitting, statistical testing, and regression analysis. Computer analysis is extensively used in conjunction with these topics. less
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