Linear Algebra is a crucial topic for understanding probability, quantum mechanics, and a whole slew of other topics in engineering and mathematics. This chapter covers amongst others the characteristic equation, diagonalization and iterative algorithms to estimate eigenvalues. Bottom line: Very well-done introduction, despite several flaws, and especially strong on applications.

If you're interested in any of these areas, preparation with this book would not only be helpful but quite fun along the way. This book has its permanent place on my work desk alongside Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering by Steven H. To be sure, there are many applications of linear algebra and it is a very useful subject, as are many aspects of math and science and related subjects. Most purchases from business sellers are protected by the Consumer Contract Regulations 2013 which give you the right to cancel the purchase within 14 days after the day you receive the item. Since 1992, he has served several terms on the national board of the Association of Christians in the Mathematical Sciences.In a flash of providential insight, young Gauss realized that the pairwise sums of numbers from both ends of the set (1+100, 2+99, 3+98) were each 101.

This leads into a chapter on eigenvalues and eigenvectors that shows applications to differential equations and spotted owls (5). I also would complain, briefly, about Strang's notation, which struck me as about the same level as his authorial voice; which is to say, somewhat limited in rigor for the sake of plainness. After this there are appendices on the uniqueness of the reduced echelon form (A) as well as complex numbers (B) for those who want additional material on these subjects, before the book concludes with a glossary, answers to odd-numbered exercises, and an index of the book's materials. I guess this is better than the opposite problem but, really, who uses a superscript H for the conjugate transpose of a matrix?This book is designed from first principles to demonstrate the importance of linear algebra through working computational examples with R and Python, including tutorials on how to install R in the Appendix. The first chapter discusses linear equations in linear algebra, introducing the book's concepts (1), which takes up the first 100 pages or so.

The best feature of this book, in my opinion, is their reference to previous theorems and results when it comes to more advanced theorems. The applications are much weaker in Strang, but the linear-spaces material is much better integrated. Lay is also co-author of several mathematics texts, including Introduction to Functional Analysis, with Angus E.

He is webmaster and newsletter editor for the MAA Southwestern Section and is an editor of the Missouri Journal of Mathematical Sciences. With traditional linear algebra texts, the course is relatively easy for students during the early stages as material is presented in a familiar, concrete setting. Meet students where they are with MyLab ®, and capture their attention in every lecture, activity, and assignment using immersive content, customized tools, and interactive learning experiences in your discipline. Strang seemed like a very nice guy when I saw him speak, but his book is no match for Lay's in terms of doing awesome things like making wonderful lists of all the 50 different statements that mean the same thing (for example: determinant of matrix is nonzero <-> matrix has full rank <-> matrix's columns are linearly independent <-> etc.