Linear Algebra and its Applications, 6th edition

  • David C. Lay, 
  • Judi J. McDonald, 
  • Steven R. Lay

Choose the option that's right for you


$9.99 / mo

4-month minimum term for $39.96

  • Access this eText title
  • Up to 2 devices
  • Discounted tutor access


$14.99 / mo

4-month minimum term for $59.96

  • Access over 1,500 titles
  • Up to 2 devices
  • Discounted tutor access

Learn more, spend less

  • Learn anytime, anywhere

    Get the app to access your eText whenever you need it

  • Make it your own

    Your notes. Your highlights. Your eText

  • Find it fast

    Quickly navigate your eText with search

  • Stay organized

    Access all your eTexts in one place

  • Easily continue access

    Keep learning with auto-renew


Linear Algebra and Its Applications fosters the concepts and skills you'll use in your future career through a modern introduction with broad, relevant applications. With traditional texts, the early stages of the course are relatively easy as material is presented in a familiar, concrete setting, but abstract concepts become a problem. Certain concepts fundamental to the study of linear algebra (such as linear independence, vector space, and linear transformations) require time to assimilate - and your understanding of them is vital.

Lay, Lay, and McDonald make these concepts more accessible by introducing them early in a familiar, concrete Rn setting, developing them gradually, and returning to them throughout the text so that you can grasp them when they are discussed in the abstract. The 6th Edition offers exciting new material, examples, and online resources, along with new topics, vignettes, and applications.

Published by Pearson (July 10th 2020) - Copyright © 2021

ISBN-13: 9780136880929

Subject: Advanced Math

Category: Linear Algebra

Table of contents

1. Linear Equations in Linear Algebra
Introductory Example: Linear Models in Economics and Engineering
1.1 Systems of Linear Equations
1.2 Row Reduction and Echelon Forms
1.3 Vector Equations
1.4 The Matrix Equation Ax = b
1.5 Solution Sets of Linear Systems
1.6 Applications of Linear Systems
1.7 Linear Independence
1.8 Introduction to Linear Transformations
1.9 The Matrix of a Linear Transformation
1.10 Linear Models in Business, Science, and Engineering
Supplementary Exercises

2. Matrix Algebra
Introductory Example: Computer Models in Aircraft Design
2.1 Matrix Operations
2.2 The Inverse of a Matrix
2.3 Characterizations of Invertible Matrices
2.4 Partitioned Matrices
2.5 Matrix Factorizations
2.6 The Leontief Input-Output Model
2.7 Applications to Computer Graphics
2.8 Subspaces of Rn
2.9 Dimension and Rank
Supplementary Exercises

3. Determinants
Introductory Example: Random Paths and Distortion
3.1 Introduction to Determinants
3.2 Properties of Determinants
3.3 Cramer's Rule, Volume, and Linear Transformations
Supplementary Exercises

4. Vector Spaces
Introductory Example: Space Flight and Control Systems
4.1 Vector Spaces and Subspaces
4.2 Null Spaces, Column Spaces, and Linear Transformations
4.3 Linearly Independent Sets; Bases
4.4 Coordinate Systems
4.5 The Dimension of a Vector Space
4.6 Change of Basis
4.7 Digital Signal Processing
4.8 Applications to Difference Equations
Supplementary Exercises

5. Eigenvalues and Eigenvectors
Introductory Example: Dynamical Systems and Spotted Owls
5.1 Eigenvectors and Eigenvalues
5.2 The Characteristic Equation
5.3 Diagonalization
5.4 Eigenvectors and Linear Transformations
5.5 Complex Eigenvalues
5.6 Discrete Dynamical Systems
5.7 Applications to Differential Equations
5.8 Iterative Estimates for Eigenvalues
5.9 Markov Chains
Supplementary Exercises

6. Orthogonality and Least Squares
Introductory Example: The North American Datum and GPS Navigation
6.1 Inner Product, Length, and Orthogonality
6.2 Orthogonal Sets
6.3 Orthogonal Projections
6.4 The Gram-Schmidt Process
6.5 Least-Squares Problems
6.6 Machine Learning and Linear Models
6.7 Inner Product Spaces
6.8 Applications of Inner Product Spaces
Supplementary Exercises

7. Symmetric Matrices and Quadratic Forms
Introductory Example: Multichannel Image Processing
7.1 Diagonalization of Symmetric Matrices
7.2 Quadratic Forms
7.3 Constrained Optimization
7.4 The Singular Value Decomposition
7.5 Applications to Image Processing and Statistics
Supplementary Exercises

8. The Geometry of Vector Spaces
Introductory Example: The Platonic Solids
8.1 Affine Combinations
8.2 Affine Independence
8.3 Convex Combinations
8.4 Hyperplanes
8.5 Polytopes
8.6 Curves and Surfaces
Supplementary Exercises

9. Optimization
Introductory Example: The Berlin Airlift
9.1 Matrix Games
9.2 Linear Programming-Geometric Method
9.3 Linear Programming-Simplex Method
9.4 Duality
Supplementary Exercises

10. Finite-State Markov Chains (Online Only)
Introductory Example: Googling Markov Chains
10.1 Introduction and Examples
10.2 The Steady-State Vector and Google's PageRank
10.3 Communication Classes
10.4 Classification of States and Periodicity
10.5 The Fundamental Matrix
10.6 Markov Chains and Baseball Statistics

A. Uniqueness of the Reduced Echelon Form
B. Complex Numbers

Your questions answered

Introducing Pearson+. Reimagined learning, designed for you. Choose from one eText or over 1,500 eTexts and study tools, all in one place, for one low monthly subscription. A new way to buy books that fits your budget. Make the most of your study time with offline access, enhanced search, notes and flashcards — to get organized, get the work done quicker and get results. Plus, with the app, put textbooks in your pocket and learn wherever. It's time to upgrade the textbook and simplify learning, so you can have time to live too.

Pearson eText is an easy-to-use digital textbook available from Pearson+. Make it your own by adding notes and highlights. Download the Pearson+ mobile app to learn on the go, even offline. Listen on the go with our new audiobook feature, available for most titles.

When you choose a plan, you're signing up for a 4-month 'term'. We will charge your payment method each month until your 4-month term has ended. You can turn on auto-renew in My account at any time to continue your subscription before your 4-month term has ended.

When you purchase a Pearson+ subscription, it will last 4 months. Before your initial 4-month term ends, you can extend your subscription by turning auto-renew on in My account. If you turn auto-renew on, we’ll automatically renew your subscription and charge you every month until you turn off auto-renew.

To avoid the next payment charge, make sure you turn auto renewal off 1 day before the auto renewal date. You can subscribe again after auto-renew has been turned off by purchasing another Pearson+ subscription. We use your credit card to renew your subscription automatically. To make sure your learning is uninterrupted, please check your card details before your first monthly payment.

With a Multi Pearson+ subscription plan, you can download up to 5 titles on the Pearson+ app from My list on each of your authorized devices every month.

When you're using your Multi Pearson+ subscription plan in a browser, you can select and read from as many titles as you like.