Mathematical Modeling: Branching Beyond Calculus reveals the versatility of mathematical modeling. The authors present the subject in an attractive manner and flexibley manner. Students will discover that the topic not only focuses on math, but biology, engineering, and both social and physical sciences.
The book is written in a way to meet the needs of any modeling course. Each chapter includes examples, exercises, and projects offering opportunities for more in-depth investigations into the world of mathematical models. The authors encourage students to approach the models from various angles while creating a more complete understanding. The assortment of disciplines covered within the book and its flexible structure produce an intriguing and promising foundation for any mathematical modeling course or for self-study.
Chapter 1: Modeling with Calculus; Exploring Extrema; Modeling with The Fundamental Theorem of Calculus; Probability Distributions; Introduction to Stochastic Processes Applications of Sequences and Series; Fibonacci and Lucas Sequences; Taylor Approximations Fourier Series and Signal Processing. Chapter 2: Modeling with Linear Algebra; Modeling with Graphs; Stochastic Models - Markov Chains; Leslie Matrices and other Matrix Models; Linear Programming; Game Theory. Chapter 3: Modeling with Programming; Simulations; Automata Models; Branching Theory. Chapter 4: Modeling with Ordinary Differential Equations; Introduction of Modeling with Differential Equations and Difference Equations; Basic Growth Models; Finding and Analyzing Equilibrium; Multiple Population Models, Coupled Systems; Epidemic Models; Models in a Variety of Fields.
