Elementary Mathematical Models: An Accessible Development without Calculus, Second Edition

Elementary Mathematical Models: An Accessible Development without Calculus, Second Edition

Author: Dan Kalman

Publisher: American Mathematical Soc.

Published: 2019-08-02

Total Pages: 528

ISBN-13: 1470450011

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Elementary Mathematical Models offers instructors an alternative to standard college algebra, quantitative literacy, and liberal arts mathematics courses. Presuming only a background of exposure to high school algebra, the text introduces students to the methodology of mathematical modeling, which plays a role in nearly all real applications of mathematics. A course based on this text would have as its primary goal preparing students to be competent consumers of mathematical modeling in their future studies. Such a course would also provide students with an understanding of the modeling process and a facility with much of the standard, non-trigonometric, content of college algebra and precalculus. This book builds, successively, a series of growth models defined in terms of simple recursive patterns of change corresponding to arithmetic, quadratic, geometric, and logistic growth. Students discover and come to understand linear, polynomial, exponential, and logarithmic functions in the context of analyzing these models of intrinsically—and scientifically—interesting phenomena including polar ice extent, antibiotic resistance, and viral internet videos. Students gain a deep appreciation for the power and limitations of mathematical modeling in the physical, life, and social sciences as questions of modeling methodology are carefully and constantly addressed. Realistic examples are used consistently throughout the text, and every topic is illustrated with models that are constructed from and compared to real data. The text is extremely attractive and the exposition is extraordinarily clear. The lead author of this text is the recipient of nine MAA awards for expository writing including the Ford, Evans, Pólya, and Allendoerfer awards and the Beckenbach Book prize. Great care has been taken by accomplished expositors to make the book readable by students. Those students will also benefit from more than 1,000 carefully crafted exercises.


Modeling Mathematical Ideas

Modeling Mathematical Ideas

Author: Jennifer M. Suh

Publisher: Rowman & Littlefield

Published: 2016-12-27

Total Pages: 227

ISBN-13: 1475817606

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Modeling Mathematical Ideas combining current research and practical strategies to build teachers and students strategic competence in problem solving.This must-have book supports teachers in understanding learning progressions that addresses conceptual guiding posts as well as students’ common misconceptions in investigating and discussing important mathematical ideas related to number sense, computational fluency, algebraic thinking and proportional reasoning. In each chapter, the authors opens with a rich real-world mathematical problem and presents classroom strategies (such as visible thinking strategies & technology integration) and other related problems to develop students’ strategic competence in modeling mathematical ideas.


An Introduction to Mathematical Modeling

An Introduction to Mathematical Modeling

Author: Edward A. Bender

Publisher: Courier Corporation

Published: 2012-05-23

Total Pages: 273

ISBN-13: 0486137120

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Employing a practical, "learn by doing" approach, this first-rate text fosters the development of the skills beyond the pure mathematics needed to set up and manipulate mathematical models. The author draws on a diversity of fields — including science, engineering, and operations research — to provide over 100 reality-based examples. Students learn from the examples by applying mathematical methods to formulate, analyze, and criticize models. Extensive documentation, consisting of over 150 references, supplements the models, encouraging further research on models of particular interest. The lively and accessible text requires only minimal scientific background. Designed for senior college or beginning graduate-level students, it assumes only elementary calculus and basic probability theory for the first part, and ordinary differential equations and continuous probability for the second section. All problems require students to study and create models, encouraging their active participation rather than a mechanical approach. Beyond the classroom, this volume will prove interesting and rewarding to anyone concerned with the development of mathematical models or the application of modeling to problem solving in a wide array of applications.


Elementary Mathematical Models

Elementary Mathematical Models

Author: Dan Kalman

Publisher: Cambridge University Press

Published: 1997

Total Pages: 374

ISBN-13: 9780883857076

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Explains the relevance and importance of mathematical modelling for a non-technical audience.


A Course in Mathematical Modeling

A Course in Mathematical Modeling

Author: Douglas D. Mooney

Publisher: American Mathematical Society

Published: 2021-11-15

Total Pages: 431

ISBN-13: 1470466163

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The emphasis of this book lies in 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 is 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.


Elementary Mathematical Modeling

Elementary Mathematical Modeling

Author: James T. Sandefur

Publisher: Brooks Cole

Published: 2003

Total Pages: 0

ISBN-13: 9780534378035

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ELEMENTARY MATHEMATICAL MODELING uses mathematics to study problems arising in areas such as Genetics, Finance, Medicine, and Economics. Throughout the course of the book, students learn how to model a real situation, such as testing levels of lead in children or environmental cleanup. They then learn how to analyze that model in relationship to the real world, such as making recommendations for minimum treatment time for children exposed to lead paint or determining the minimum time required to adequately clean up a polluted lake. Often the results will be counterintuitive, such as finding that an increase in the rate of wild-life harvesting may actually decrease the long-term harvest, or that a lottery prize that is paid out over a number of years is worth far less than its advertised value. This use of mathematics illustrates and models real-world issues and questions, bringing the value of mathematics to life for students, enabling them to see, perhaps for the first time, the utility of mathematics.


Becoming a Teacher of Mathematical Modeling

Becoming a Teacher of Mathematical Modeling

Author: Elizabeth G. Arnold

Publisher: National Council of Teachers of English

Published: 2021

Total Pages: 0

ISBN-13: 9781680540468

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This book explores what it means to teach modeling. In part I, the authors discuss mathematical modeling broadly and allow you to explore the student practices and perspectives involved, how modeling can empower students, and classroom communities that support modeling. In part II, the authors launch you on your journey of becoming a teacher of modeling by illustrating features of modeling that are evident in the classrooms of teacher who engage their students in modeling and by sharing specific strategies for making modeling a part of your own classroom practices. In part III, they examine the complementary perspectives of mathematical and statistical models, the role of modeling in the secondary mathematics curriculum, and the role of technology in supporting modeling. Finally, they share wisdom from other teachers who have engaged in this journey and invite you to join in the modeling community.


A Biologist's Guide to Mathematical Modeling in Ecology and Evolution

A Biologist's Guide to Mathematical Modeling in Ecology and Evolution

Author: Sarah P. Otto

Publisher: Princeton University Press

Published: 2011-09-19

Total Pages: 745

ISBN-13: 1400840910

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Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork. In this book, Sarah Otto and Troy Day provide biology students with the tools necessary to both interpret models and to build their own. The book starts at an elementary level of mathematical modeling, assuming that the reader has had high school mathematics and first-year calculus. Otto and Day then gradually build in depth and complexity, from classic models in ecology and evolution to more intricate class-structured and probabilistic models. The authors provide primers with instructive exercises to introduce readers to the more advanced subjects of linear algebra and probability theory. Through examples, they describe how models have been used to understand such topics as the spread of HIV, chaos, the age structure of a country, speciation, and extinction. Ecologists and evolutionary biologists today need enough mathematical training to be able to assess the power and limits of biological models and to develop theories and models themselves. This innovative book will be an indispensable guide to the world of mathematical models for the next generation of biologists. A how-to guide for developing new mathematical models in biology Provides step-by-step recipes for constructing and analyzing models Interesting biological applications Explores classical models in ecology and evolution Questions at the end of every chapter Primers cover important mathematical topics Exercises with answers Appendixes summarize useful rules Labs and advanced material available


Learning How to Teach Mathematical Modeling in School and Teacher Education

Learning How to Teach Mathematical Modeling in School and Teacher Education

Author: Rita Borromeo Ferri

Publisher: Springer

Published: 2017-11-26

Total Pages: 163

ISBN-13: 3319680722

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This timely resource fills a gap in existing literature on mathematical modeling by presenting both theory- and evidence-based ideas for its teaching and learning. The book outlines four key professional competencies that must be developed in order to effectively and appropriately teach mathematical modeling, and in so doing it seeks to reduce the discrepancies between educational policy and educational research versus everyday teaching practice. Among the key competencies covered are: Theoretical competency for practical work. Task competency for instructional flexibility. Instructional competency for effective and quality lessons. Diagnostic competency for assessment and grading. Learning How to Teach Mathematical Modeling in School and Teacher Education is relevant to practicing and future mathematics teachers at all levels, as well as teacher educators, mathematics education researchers, and undergraduate and graduate mathematics students interested in research based methods for teaching mathematical modeling.


Introduction to Mathematical Modeling

Introduction to Mathematical Modeling

Author: Mayer Humi

Publisher: CRC Press

Published: 2017-09-19

Total Pages: 418

ISBN-13: 1498728022

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Introduction to Mathematical Modeling helps students master the processes used by scientists and engineers to model real-world problems, including the challenges posed by space exploration, climate change, energy sustainability, chaotic dynamical systems and random processes. Primarily intended for students with a working knowledge of calculus but minimal training in computer programming in a first course on modeling, the more advanced topics in the book are also useful for advanced undergraduate and graduate students seeking to get to grips with the analytical, numerical, and visual aspects of mathematical modeling, as well as the approximations and abstractions needed for the creation of a viable model.