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Matrix Algebra: Theory, Computations and Applications in Statistics (Springer Texts in Statistics)
ANG 240
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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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Productdetails
| 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) |
Voor wie is dit geschikt?
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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.
PRODUCTBESCHRIJVING
Matrix Algebra: Theory, Computations and Applications in Statistics (Springer Texts in Statistics)
Vragen & Antwoorden van klanten
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Is this book suitable for beginners?
antwoord: This textbook is designed for graduate and advanced undergraduate students already familiar with basic concepts. -
vraag:
Do I need to know programming to use this textbook?
antwoord: Some understanding of programming in Fortran or C, or using R or Matlab is beneficial for the numerical linear algebra section. -
vraag:
What changes were made in the second edition?
antwoord: The second edition includes 100 pages of new material, 30 additional exercises, and new discussions on vectors and statistical applications.
Probability & Statistics Editorial Review
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- Clear and comprehensive explanations
- Well-structured for learning
- Numerous practical examples
- Strong focus on applications
- Engaging writing style
Nadelen
- Some sections are a bit dense.
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ANG 240
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Kenmerken en voordelen
- 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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