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Item #:
210910921
Matrix Algebra: Theory, Computations and Applications in Statistics (Springer Texts in Statistics)
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Item #:
210910921
SAR 498
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Matrix algebra is one of the most important areas of mathematics in data science and statistical theory, providing essential updates and comprehensive coverage on critical topics.
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What Stands Out
Comprehensive Coverage
This book offers an extensive exploration of matrix algebra, making it an essential resource for students and professionals in statistics and data science. It covers fundamental concepts and advanced applications thoroughly.
Practical Applications
It connects theoretical concepts to real-world applications, helping readers understand how matrix algebra is used in statistical modeling and data analysis, thereby enhancing practical skills and knowledge.
User-Friendly Format
The Kindle edition provides easy navigation and access to hyperlinks, allowing for efficient studying and reference. Its well-structured content caters to both beginners and experienced researchers.
Product Details
| Publisher | Springer |
| Publication date | October 12, 2017 |
| Edition | 2nd |
| Language | English |
| File size | 13.4 MB |
| Enhanced typesetting | Not Enabled |
| X-Ray for textbooks | Enabled |
| Word Wise | Not Enabled |
| Print length | 677 pages |
| Format | Print Replica |
| ISBN-13 | 978-3319648675 |
| Page Flip | Not Enabled |
| Part of series | Springer Texts in Statistics |
| Item Weight | 1 lbs (450 grams) |
Who Should Buy?
-
Statistics Students
Ideal for students seeking to understand matrix algebra concepts used in statistical applications and computations.
-
Data Scientists
Beneficial for data professionals needing matrix algebra for data analysis and statistical modeling in their work.
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Researchers
Helpful for researchers in statistics requiring deep theoretical knowledge and computational techniques for matrix algebra.
-
Beginners
Not suitable for absolute beginners in algebra, as it assumes prior knowledge of matrix concepts.
Product Description
Matrix Algebra: Theory, Computations and Applications in Statistics (Springer Texts in Statistics)
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Pros
- Clear and comprehensive explanations
- Well-structured for learning
- Numerous practical examples
- Strong focus on applications
- Engaging writing style
Cons
- Some sections are a bit dense.
Product Price History
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SAR 498
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Features & Benefits
- Comprehensive coverage of matrix algebra for statistical applications.
- Includes updates and additional material in the second edition.
- Ideal for graduate and advanced undergraduate students.
- Covers various types of matrices and their special properties.
- Focus on numerical linear algebra and efficient algorithms.
- Supplementary text for courses in linear models and statistical computing.
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