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Item #:
210910921
Matrix Algebra: Theory, Computations and Applications in Statistics (Springer Texts in Statistics)
Item #:
210910921
BHD 52
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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
| Country of Origin | This item will be imported from US |
| Item Weight | 1 lbs (450 grams) |
| What is in the box | Matrix Algebra: Theory, Computations... For more details, please check description/product details |
Who Should Buy?
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Statistics Students
Ideal for students seeking to understand matrix algebra concepts used in statistical applications and computations.
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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.
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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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Is this book suitable for beginners?
Answer: This textbook is designed for graduate and advanced undergraduate students already familiar with basic concepts. -
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Do I need to know programming to use this textbook?
Answer: Some understanding of programming in Fortran or C, or using R or Matlab is beneficial for the numerical linear algebra section. -
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What changes were made in the second edition?
Answer: The second edition includes 100 pages of new material, 30 additional exercises, and new discussions on vectors and statistical applications.
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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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