This text makes a great supplement and provides a systematic approach for teaching undergraduate and graduate students how to read, understand, think about, and do proofs. The approach is to categorize, identify, and explain (at the student′s level) the various techniques that are used repeatedly in all proofs, regardless of the subject in which the proofs arise. How to Read and Do Proofs also explains when each technique is likely to be used, based on certain key words that appear in the problem under consideration. Doing so enables students to choose a technique consciously, based on the form of the problem.
A guide that shows how to read, understand, and do proofs. It shows how any proof can be understood as a sequence of techniques. It covers a range of techniques used in proofs, such as the contrapositive, induction, and proof by contradiction.
Here is a unique book that reduces the time & frustration involved in learning virtually every college-level undergraduate mathematics course & is as appropriate for freshman as it is for seniors. Standard textbooks teach specific subject matter, but this book explains for the first time the underlying thinking processes used in all of these courses. This book is therefore suitable as a supplement & as a reference for all of the following courses: discrete mathematics, linear algebra, abstract algebra, real analysis, transition-to-advanced math courses, courses on proofs & mathematical reasoning, & many more. There is currently no book on the market like this. You will not be able to keep this book on the shelf, but do not take our word for it -- Ask the head of your math department about this book. Distributed by BookMasters Distribution Center, P.O. Box 388, 1444 St. Route 42, Ashland, OH 44805. Phone (800) 247-6553, FAX (419) 281-6883.
This text focuses on teaching the "thinking process" used in quantitative decision making. Its unique approach emphasizes the building of optimization models before plugging in of data. In this way, students have a better understanding of their results. To challenge the students to understand the problem, a greater emphasis is given to a conceptual approach to each solution procedure. Heavy amphasis in also given to computer analysis and interpreting computer outputs for solving decision problems.
Suitable for undergraduate students of mathematics and graduate students of operations research and engineering, this text covers the basic theory and computation for a first course in linear programming. In addition to substantial material on mathematical proof techniques and sophisticated computation methods, the treatment features numerous examples and exercises.
An introductory chapter offers a systematic and organized approach to problem formulation. Subsequent chapters explore geometric motivation, proof techniques, linear algebra and algebraic steps related to the simplex algorithm, standard phase 1 problems, and computational implementation of the simplex algorithm. Additional topics include duality theory, issues of sensitivity and parametric analysis, techniques for handling bound constraints, and network flow problems. Helpful appendixes conclude the text, including a new addition that explains how to use Excel to solve linear programming problems.