A Beginner’s Guide to Mathematical Proof

Author:   Mark J. DeBonis (Manhattan College, USA)
Publisher:   Taylor & Francis Ltd
ISBN:  

9781032687704


Pages:   160
Publication Date:   31 March 2025
Format:   Paperback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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A Beginner’s Guide to Mathematical Proof


Overview

A Beginner’s Guide to Mathematical Proof prepares mathematics majors for the transition to abstract mathematics, as well as introducing a wider readership of quantitative science students, such as engineers, to the mathematical structures underlying more applied topics. The text is designed to be easily utilized by both instructor and student, with an accessible, step-by-step approach requiring minimal mathematical prerequisites. The book builds towards more complex ideas as it progresses but never makes assumptions of the reader beyond the material already covered. Features No mathematical prerequisites beyond high school mathematics Suitable for an Introduction to Proofs course for mathematics majors and other students of quantitative sciences, such as engineering Replete with exercises and examples

Full Product Details

Author:   Mark J. DeBonis (Manhattan College, USA)
Publisher:   Taylor & Francis Ltd
Imprint:   Chapman & Hall/CRC
Weight:   0.560kg
ISBN:  

9781032687704


ISBN 10:   1032687703
Pages:   160
Publication Date:   31 March 2025
Audience:   College/higher education ,  Tertiary & Higher Education
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Preface, Chapter 1 Mathematical Logic, Chapter 2 Methods of Proof, Chapter 3 Special Proof Types, Chapter 4 Foundational Mathematical Topics, References, Index

Reviews

“Exceptionally well organized and presented, as well as thoroughly replete with student friendly exercises and examples” --Midwest Book Review


Author Information

Mark DeBonis received his PhD in Mathematics from University of California, Irvine, USA. He began his career as a theoretical mathematician in the field of group theory and model theory, but in later years switched to applied mathematics, in particular to machine learning. He spent some time working for the US Department of Energy at Los Alamos National Lab as well as the US Department of Defense at the Defense Intelligence Agency as an applied mathematician of machine learning. He is at present working for the US Department of Energy at Sandia National Lab. His research interests include machine learning, statistics and computational algebra.

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