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Linear algebra and its applications / David C. Lay.

By: Material type: TextTextPublication details: Noida : Pearson India Education Services Pvt. Ltd, c2023.Edition: 5th edDescription: xi, 494, [68] p. : ill. (some col.) ; 26 cmISBN:
  • 9789357059688
Subject(s): DDC classification:
  • 512.5 LAY 23rd
LOC classification:
  • QA184.2 .L39 2012
Online resources:
Contents:
Linear Equations in Linear Algebra. Matrix Algebra. Determinants. Vector Spaces. Eigenvalues and Eigenvectors. Orthogonality and Least-Squares. Symmetric Matrices and Quadratic Forms.
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Reference Book VIT-AP Reference 512.5 LAY (Browse shelf(Opens below)) Not for loan MATH 022413
Text Book VIT-AP General Stacks 512.5 LAY (Browse shelf(Opens below)) Checked out to GUDIMELLA SHANMUKHI MYDHILI (24BCB7125) MATH 2025-05-19 022414
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Text Book VIT-AP General Stacks 512.5 LAY (Browse shelf(Opens below)) Checked out to POOJA KUMARI (24BCB7078) MATH 2025-05-24 022416
Text Book VIT-AP General Stacks 512.5 LAY (Browse shelf(Opens below)) Checked out to ANGELINA CHATTERJEE (24BCB7082) MATH 2025-05-24 022417
Text Book VIT-AP General Stacks 512.5 LAY (Browse shelf(Opens below)) In transit from VIT-AP to School of Advanced Studies-Maths Section since 2025-05-13 MATH 022418
Text Book VIT-AP General Stacks 512.5 LAY (Browse shelf(Opens below)) In transit from VIT-AP to School of Advanced Studies-Maths Section since 2025-05-10 MATH 022419
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Text Book VIT-AP General Stacks 512.5 LAY (Browse shelf(Opens below)) In transit from VIT-AP to School of Advanced Studies-Maths Section since 2025-05-06 MATH 022421

Includes index.

Linear Equations in Linear Algebra.

Matrix Algebra.

Determinants.

Vector Spaces.

Eigenvalues and Eigenvectors.

Orthogonality and Least-Squares.

Symmetric Matrices and Quadratic Forms.

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. However, when abstract concepts are introduced, students often hit a wall. Instructors seem to agree that certain concepts (such as linear independence, spanning, subspace, vector space, and linear transformations) are not easily understood and require time to assimilate. These concepts are fundamental to the study of linear algebra, so students' understanding of them is vital to mastering the subject. This text makes 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 when they are discussed in the abstract, students are readily able to understand.

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