The third edition of this widely popular textbook is authored by a master teacher. This book provides a mathematically rigorous introduction to analysis of real valued functions of one variable. This intuitive, student-friendly text is written in a manner that will help to ease the transition from primarily computational to primarily theoretical mathematics. The material is presented clearly and as intuitive as possible while maintaining mathematical integrity. The author supplies the ideas of the proof and leaves the write-up as an exercise. The text also states why a step in a proof is the reasonable thing to do and which techniques are recurrent. Examples, while no substitute for a proof, are a valuable tool in helping to develop intuition and are an important feature of this text. Examples can also provide a vivid reminder that what one hopes might be true is not always true. Features of the Third Edition: Begins with a discussion of the axioms of the real number system. The limit is introduced via sequences. Examples motivate what is to come, highlight the need for hypothesis in a theorem, and make abstract ideas more concrete. A new section on the Cantor set and the Cantor function. Additional material on connectedness. Exercises range in difficulty from the routine "getting your feet wet" types of problems to the moderately challenging problems. Topology of the real number system is developed to obtain the familiar properties of continuous functions. Some exercises are devoted to the construction of counterexamples. The author presents the material to make the subject understandable and perhaps exciting to those who are beginning their study of abstract mathematics. Table of Contents Preface Introduction The Real Number System Sequences of Real Numbers Topology of the Real Numbers Continuous Functions Differentiation Integration Series of Real Numbers Sequences and Series of Functions Fourier Series Bibliography Hints and Answers to Selected Exercises Index Biography James R. Kirkwood holds a Ph.D. from University of Virginia. He has authored fifteen, published mathematics textbooks on various topics including calculus, real analysis, mathematical biology and mathematical physics. His original research was in mathematical physics, and he co-authored the seminal paper in a topic now called Kirkwood-Thomas Theory in mathematical physics. During the summer, he teaches real analysis to entering graduate students at the University of Virginia. He has been awarded several National Science Foundation grants. His texts, Elementary Linear Algebra, Linear Algebra, and Markov Processes, are also published by CRC Press.

Linear Algebra, James R. Kirkwood and Bessie H. Kirkwood, 978-1-4987-7685-1, K29751 Shelving Guide: Mathematics This text has a major focus on demonstrating facts and techniques of linear systems that will be invaluable in higher mathematics and related fields. A linear algebra course has two major audiences that it must satisfy. It provides an important theoretical and computational tool for nearly every discipline that uses mathematics. It also provides an introduction to abstract mathematics. This book has two parts. Chapters 1-7 are written as an introduction. Two primary goals of these chapters are to enable students to become adept at computations and to develop an understanding of the theory of basic topics including linear transformations. Important applications are presented. Part two, which consists of Chapters 8-14, is at a higher level. It includes topics not usually taught in a first course, such as a detailed justification of the Jordan canonical form, properties of the determinant derived from axioms, the Perron-Frobenius theorem and bilinear and quadratic forms. Though users will want to make use of technology for many of the computations, topics are explained in the text in a way that will enable students to do these computations by hand if that is desired. Key features include: Chapters 1-7 may be used for a first course relying on applications Chapters 8-14 offer a more advanced, theoretical course Definitions are highlighted throughout MATLAB (R) and R Project tutorials in the appendices Exercises span a range from simple computations to fairly direct abstract exercises Historical notes motivate the presentation

Elementary Linear Algebra is written for the first undergraduate course. The book focuses on the importance of linear algebra in many disciplines such as engineering, economics, statistics, and computer science. The text reinforces critical ideas and lessons of traditional topics. More importantly, the book is written in a manner that deeply ingrains computational methods.

Elementary Linear Algebra is written for the first undergraduate course. The book focuses on the importance of linear algebra in many disciplines such as engineering, economics, statistics, and computer science. The text reinforces critical ideas and lessons of traditional topics. More importantly, the book is written in a manner that deeply ingrains computational methods.

Designed as supplemental material to the textbook An Invitation to Biomathematics, this laboratory manual expertly aids students who wish to gain a deeper understanding of solving biological issues with computer programs. This manual provides hands-on exploration of model development, model validation, and model refinement, enabling students to truly experience advancements made in biology by mathematical models. Each of the projects offered can be used as individual module in traditional biology or mathematics courses such as calculus, ordinary differential equations, elementary probability, statistics, and genetics.
This manual is a companion to the textbook, An Invitation of Biomathematics (sold separately ISBN: 0120887711; or as a set ISBN: 0123740290).
* Can be used as a computer lab component of a course in biomathematics or as homework projects for independent student work
* Biological topics include: Ecology, Toxicology, Microbiology, Epidemiology, Genetics, Biostatistics, Physiology, Cell Biology, and Molecular Biology
* Mathematical topics include: Discrete and continuous dynamical systems, difference equations, differential equations, probability distributions, statistics, data transformation, risk function, statistics, approximate entropy, periodic components, and pulse-detection algorithms
* Includes more than 120 exercises derived from ongoing research studies

Today, virtually any advance in the life sciences requires a sophisticated mathematical approach. The methods of mathematics and computer science have emerged as critical tools to modeling biological phenomena, understanding patterns, and making sense of large data sets, such as those generated by the human genome project. An Invitation to Biomathematics provides a comprehensive, yet easily digested entry into the diverse world of mathematical biology--the union of biology, mathematics, and computer science.
This textbook, expertly written by a team of experienced educators, is divided into two parts. The first section presents core principles as elucidated by classical problems such as population growth, predator-prey interactions, epidemic models, and population genetics, while the second applies these principles to modern biomedical research. In addition, the supplementary work Laboratory Manual of Biomathematics (available separately) is designed to enable hands-on exploration of model development, model validation, and model refinement.
* Provides a complete guide for development of quantification skills crucial for applying mathematical methods to biological problems.
* Includes well-known examples from across disciplines in the life sciences including modern biomedical research.
* Explains how to use data sets or dynamical processes to build mathematical models.
* Offers extensive illustrative materials.
* Written in clear and easy-to-follow language without assuming a background in math or biology.
* A laboratory manual is available for hands-on, computer-assisted projects based on material covered in the text.

Clear, rigorous, and intuitive, Markov Processes provides a bridge from an undergraduate probability course to a course in stochastic processes and also as a reference for those that want to see detailed proofs of the theorems of Markov processes. It contains copious computational examples that motivate and illustrate the theorems. The text is designed to be understandable to students who have taken an undergraduate probability course without needing an instructor to fill in any gaps. The book begins with a review of basic probability, then covers the case of finite state, discrete time Markov processes. Building on this, the text deals with the discrete time, infinite state case and provides background for continuous Markov processes with exponential random variables and Poisson processes. It presents continuous Markov processes which include the basic material of Kolmogorov's equations, infinitesimal generators, and explosions. The book concludes with coverage of both discrete and continuous reversible Markov chains. While Markov processes are touched on in probability courses, this book offers the opportunity to concentrate on the topic when additional study is required. It discusses how Markov processes are applied in a number of fields, including economics, physics, and mathematical biology. The book fills the gap between a calculus based probability course, normally taken as an upper level undergraduate course, and a course in stochastic processes, which is typically a graduate course.