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Linear algebra and its applications

By:

Lay, David C

Contributor(s):

Material type: Text

9780321982384

Subject(s):

DDC classification:

REF 512.5 LAY-L

Contents:

1. Linear equations in linear algebra

2. Matrix algebra

3. Determinants

4. Vector spaces

5. Eigenvalues and eigenvectors

6. Orthogonality and least squares

7. Symmetric matrices and quadratic forms

8. The geometry of vector spaces

9. Optimization (online)

10. Finite-state markov chains (online)

Summary: For courses in linear algebra. 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.

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Holdings
Item type	Current library	Collection	Call number	Status	Notes	Date due	Barcode	Item holds
Books	IIITD Reference	Mathematics	REF 512.5 LAY-L (Browse shelf(Opens below))	Not for loan	Gifted by Mehak Gopal (2021475)		G02810

Total holds: 0

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Previous	REF 512.5 KUM-L Linear algebra: a geometric approach	REF 512.5 LAY-L Linear algebra and its applications	REF 512.5 LAY-L Linear algebra and its applications	REF 512.5 LAY-L Linear algebra and its applications	REF 512.5 LIP-L Schaum's outline of the theory and problems of linear algebra	REF 512.5 MAT-T Thirty-three miniatures : mathematical and algorithmic applications of linear algebra	REF 512.5 MEY-M Matrix analysis and applied linear algebra	Next

Includes index

1. Linear equations in linear algebra

2. Matrix algebra

3. Determinants

4. Vector spaces

5. Eigenvalues and eigenvectors

6. Orthogonality and least squares

7. Symmetric matrices and quadratic forms

8. The geometry of vector spaces

9. Optimization (online)

10. Finite-state markov chains (online)

For courses in linear algebra. 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.

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