Exploring Linear Algebra
Labs and Projects with Mathematica (R)
2nd Edition
Published on 26. February 2025
164 pages
978-1-040-31146-2 (ISBN)
Description
This text focuses on the primary topics in a first course in Linear Algebra. The author includes additional advanced topics related to data analysis, singular value decomposition, and connections to differential equations. This is a lab text that would lead a class through Linear Algebra using Mathematica (R) demonstrations and Mathematica (R) coding.
The book includes interesting examples embedded in the projects. Examples include the discussions of "Lights Out", Nim, the Hill Cipher, and a variety of relevant data science projects.
The 2nd Edition contains:
Additional Theorems and Problems for students to prove/disprove (these act as theory exercises at the end of most sections of the text)
Additional sections that support Data Analytics techniques, such as Kronecker sums and products, and LU decomposition of the Vandermonde matrix
Updated and expanded end-of-chapter projects
Instructors and students alike have enjoyed this popular book, as it offers the opportunity to add Mathematica (R) to the Linear Algebra course.
I would definitely use the book (specifically the projects at the end of each section) to motivate undergraduate research.-Nick Luke, North Carolina A&T State University.
The book includes interesting examples embedded in the projects. Examples include the discussions of "Lights Out", Nim, the Hill Cipher, and a variety of relevant data science projects.
The 2nd Edition contains:
Additional Theorems and Problems for students to prove/disprove (these act as theory exercises at the end of most sections of the text)
Additional sections that support Data Analytics techniques, such as Kronecker sums and products, and LU decomposition of the Vandermonde matrix
Updated and expanded end-of-chapter projects
Instructors and students alike have enjoyed this popular book, as it offers the opportunity to add Mathematica (R) to the Linear Algebra course.
I would definitely use the book (specifically the projects at the end of each section) to motivate undergraduate research.-Nick Luke, North Carolina A&T State University.
More details
Series
Edition
2nd edition
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
ISBN-13
978-1-040-31146-2 (9781040311462)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
02/2025
2nd Edition
Chapman & Hall/CRC
€186.70
Shipment within 10-20 days
Book
02/2025
2nd Edition
Chapman & Hall/CRC
€76.30
Shipment within 10-20 days
Book
02/2025
CRC Press
Unfortunately, price unknown
Available (delivery time upon request)
Person
Dr. Crista Arangala is Professor of Mathematics and Chair of the Department of Mathematics and Statistics at Elon University in North Carolina. She has been teaching and researching in a variety of fields, including inverse problems, applied partial differential equations, applied linear algebra, mathematical modeling, and service learning education. She runs a traveling science museum with her Elon University students in Kerala, India. Dr. Arangala was chosen to be a Fulbright Scholar in 2014 as a visiting lecturer at the University of Colombo where she continued her projects in inquiry learning in Linear Algebra and began working with a modeling team focusing on Dengue fever research. Dr. Arangala has published several textbooks that implore inquiry learning techniques, including Exploring Linear Algebra: Labs and Projects with MATLAB (R), Mathematical Modeling: Branching Beyond Calculus, and Linear Algebra with Machine Learning and Data.
Content
1. Matrix Operations
2. Invertibility
3. Vector Spaces
4. Orthogonality
5. Matrix Decomposition with Applications
6. Applications to Differential Equations
2. Invertibility
3. Vector Spaces
4. Orthogonality
5. Matrix Decomposition with Applications
6. Applications to Differential Equations
