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Concepts of Mathematical Modeling,9780486435152
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Concepts of Mathematical Modeling


Author(s): Walter J. Meyer
ISBN10:  0486435156
ISBN13:  9780486435152
Format:  Paperback
Pub. Date:  8/13/2004
Publisher(s): Dover Publications

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SummaryTable of Contents
Appropriate for undergraduate and graduate students, this text features independent sections that illustrate the most important principles of mathematical modeling, a variety of applications, and classic models. Students with a solid background in calculus and some knowledge of probability and matrix theory will find the material entirely accessible. The range of subjects includes topics from the physical, biological, and social sciences, as well as those of operations research. Discussions cover related mathematical tools and the historical eras from which the applications are drawn. Each section is preceded by an abstract and statement of prerequisites, and answers or hints are provided for selected exercises. 1984 ed.
Preface v
Chapter 1 The Scope of Mathematical Modeling 1(68)
1 Models, Mathematical and Otherwise
1(12)
2 Steps in Building a Mathematical Model
13(10)
3 Approximate and Limited Models-Gravity, Rockets, and Raindrops
23(16)
4 Macro and Micro Population Models I-Exponential Growth
39(4)
5 Macro and Micro Population Models II-The Leslie Matrix
43(10)
6 Macro and Micro Population Models III-Family-Planning Models
53(7)
7 Descriptive and Prescriptive Models-Inventory Policy
60(9)
Chapter 2 The Relation of Models to Data 69(70)
1 Sources of Error-Underground Exploration of the Earth
69(12)
2 Adjusting Data I (The Easy Way)-The Mean and the Maximum Likelihood
81(19)
3 Adjusting Data 11 (The Hard Way)-Miscellaneous Methods and Examples
100(21)
4 Testing Models-Weighted-Voting Games
121(11)
5 Putting the Facts in Order-Mendeleev and the Periodic Table
132(7)
Chapter 3 Evaluation of Mathematical Models 139(97)
1 A Bird's-Eye View of Evaluation-College Enrollment
139(11)
2 Descriptive Realism-Simple Linear Regression
150(20)
3 Descriptive Realism-Correlation Is Not Causation
170(10)
4 Accuracy-Multiple Linear Regression
180(18)
5 Precision-Malthus and the Dismal Theorem
198(13)
6 Generality and Fruitfulness-From Astrology to Technology with Kepler and Newton
211(11)
7 Robustness-The Ups and Downs of Ancient Astronomy
222(14)
Chapter 4 Optimization 236(74)
1 Classical Optimization
236(10)
2 Linear Programming-Formulation and Graphical Solution
246(20)
3 An Outline of the Simplex Method
266(8)
4 Integer Programming-The Knapsack and Traveling Salesman Problems
274(8)
5 The Transportation Problem
282(16)
6 Combinatorial Optimization-The Chinese Postman Problem
298(12)
Chapter 5 Choosing the Mathematics for the Model 310(103)
1 Simulation versus Analytic Solution-Queueing Up in the Doctor's Waiting Room
310(14)
2 Discrete versus Continuous Models
324(52)
2A Introduction to Difference Equations
325(6)
2B Exponential Population Growth-Difference and Differential Equations
331(8)
2C Logistic Population Growth-Difference and Differential Equations
339(6)
2D Equilibrium, Stable and Unstable
345(9)
2E Stability of Linear Difference Equations-Commodity Prices and Cobweb Analysis
354(9)
2F Stability of Some Nonlinear Difference Equations-Logistic Population Growth
363(13)
3 Deterministic versus Stochastic Models-Forecasting Epidemics
376(37)
3A An Outline of Probability
377(15)
3B A Day in the Life of an Epidemic-Stochastic and Deterministic Views
392(8)
3C The Lifetime of a Deterministic Epidemic
400(5)
3D The Lifetime of a Simple Stochastic Epidemic
405(8)
Appendix 413(4)
Answers to Selected Exercises 417(16)
Index 433

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