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Matrix Algebra: Theory, Computations and Applications in Statistics (Springer Texts in Statistics)
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.
Matrix Algebra: Theory, Computations and Applications in Statistics (Springer Texts in Statistics)
Item #: 210910921

Matrix Algebra: Theory, Computations and Applications in Statistics (Springer Texts in Statistics)

Item #: 210910921

€ 121

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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

Shop Matrix Algebra: Theory, Computations and Applications in Statistics (Springer Texts in Statistics) online at a best price in Montenegro. B077NH917X
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 Weight1 lbs (450 grams)

Who Should Buy?

Suitable For
  • 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.

  • Researchers

    Helpful for researchers in statistics requiring deep theoretical knowledge and computational techniques for matrix algebra.

Not Suitable For
  • 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.

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