Linear Algebra Demystified

by David McMahon

Book Overview

Taught at junior level math courses at every university, Linear Algebra is essential for students in almost every technical and analytic discipline.

• Format: Paperback
• Language: English
• ISBN: 0071465790
• ISBN13: 9780071465793
• Release Date: November 2005
• Publisher: McGraw-Hill Companies
• Length: 255 Pages
• Weight: 1.10 lbs.
• Dimensions: 0.7" x 7.3" x 9.2"

Customer Reviews

A great book for students

This book is really clear. It's a lot easier to understand than the book we are using for the class and has helped me grasp the lectures better.

Love this Book!

I recently took an online Linear Algebra class, and I was struggling to understand the material since everything was self-taught and my textbook was aweful. I started searching for an aid to help me understand the material better to get me through my mid-term and final, and I only had two weeks to teach myself a whole semester's worth of the stuff. This book was an absolute lifesaver! He goes through every aspect of Linear Algebra that I needed to know, and often gave a much simplier way to solve problems than my textbook had presented. I now have a good understanding of the subject, and I got a B in my class. This book doesn't just give you formulas or a straight way to solve the problem, he walks you through different types you might come across and if you do the quizzes and the final exam in the back then you will definitely be prepared. I plan on buying more of his books the next time I have trouble in a class!

One of the hottest books on Linear Algebra

If your looking for a book to supplement your textbook on Linear Algebra, or a book that provides a mathematical background for a course in Quantum Physics, check out this book. Many textbooks seem to be written at a level that requires the reader to already have a solid understanding of the material being presented. If you don't, you struggle through the book. How many times have you started a chapter on Vector Spaces, Linear Equations, or Matices, only to be lost after the first page or two. David McMahon does an excellent job of giving clear, step-by-step examples, as he walks you through Linear Equations, Matrix Algebra, Determinants, Vectors Spaces, and Eigenvectors. And here's the thing, you understand each topic, as you complete it. I have nothing but the highest praise for David McMahon as an author, who took the essentials of linear algebra, and presented it in a format that is easy to understand, and at the same time fun. If you agree with this review, and are interested in building on what you learned in "Linear Algebra DeMystified", check out David McMahon's two other books, "Quantum Mechanics DeMystified" and "Relativity DeMystified".

Neo Matrix

The explainations and examples are better than the text used in my class. Unfortunately, the notations and terminology don't always match our text. If it were up to me, Linear Algebra Demystified would be our primary text. The one I have now should only be used for the excercises. I am a tutor. Many of my students use the Demystified series to help themselves with math and science. We all recommend the books to each other. Now, I'm recommending them to you!

A pleasant surprise

After reading the author's other book Quantum Mechanics Demystified, I was curious about this work. I was quite surprised. The author's talents are topic selection and presentation. It seems linear algebra books are either theoretical or applied. While this book is clearly of the applied flavor, it steals the gems from the theoretical presentations. Most people who have had linear algebra and are not math majors see matrices as collections of numbers to solve linear systems. While the author covers the solution of linear systems, he shows that Gaussian elimination is a form of reduction which tells us about the problem, not just the solution. By the time you get through QR reduction and singular value decomposition (SVD), you will think of linear algebra in a broader sense. To me this volume corrects a common problem where practitioners think linear algebra = Gaussian elimination + determinants. He brings in the practical perspective from advanced treatments without a cumbersome theoretical framework. As for the quality of the presentation, I must say that when I compared the SVD presentation in LAD to that in Numerical Recipes, I had a strong preference for LAD. By way of critique, I would encourage the author to rework his problems so that they have integer solutions; the manipulation of complex fractions is tedious and detracts from the clarity of the presentation. In closing, this book collects the material you should have in your mind after completing a class in linear algebra.