Linear Algebra and Its Applications
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€ 173
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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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What Stands Out
Produkto Aprašymas
| Publisher | Pearson |
| Publication date | December 24, 2014 |
| Edition | 5th |
| Language | English |
| Print length | 576 pages |
| ISBN-10 | 9780321982384 |
| ISBN-13 | 978-0321982384 |
| Item Weight | 2.69 pounds (1.22 kg) |
| Dimensions | 8.25 x 1.05 x 10.3 inches (21 x 2.7 x 26.2 cm) |
Who Should Buy?
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Students
Ideal for undergraduate and graduate students seeking a comprehensive understanding of linear algebra concepts and applications.
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Instructors
Useful for educators looking to enhance their teaching with robust examples and a clear pedagogical approach.
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Self-Learners
Great for individuals aiming to independently study linear algebra, featuring diverse exercises and applications in different fields.
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Beginners
Not suitable for complete beginners; prior knowledge of basic mathematics is required for proper comprehension of concepts.
PRODUKTO APRAŠYMAS
Linear Algebra and Its Applications
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Mathematics Editorial Review
The 5th Edition of Linear Algebra and Its Applications is a well-made and thought-out textbook for a first course in Linear Algebra. It is highly recommended for its quality and effectiveness in teaching the subject. Despite some highlighting, the book is in good condition and is a valuable resource for learning.
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Argumentai
- Well-made and thought-out textbook
- Effective in teaching Linear Algebra
- Good quality
Minusai
- Some highlighting
Product Price History
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€ 173
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Savybės ir privalumai
- Introduces and develops concepts gradually in a familiar context
- Students can readily understand abstract concepts
- Understanding fundamental concepts is vital
- Concepts are reintroduced throughout the text
- Balances familiar and abstract settings
- Includes linear independence, spanning, subspace, vector space, and linear transformations
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