Probability and Mathematical Statistics: Theory, Applications, and Practice in R
This book develops the theory of probability and mathematical statistics with the goal of analyzing real-world data.
Probability and Mathematical Statistics: Theory, Applications, and Practice in R
Numéro d'article: 43464224

Probability and Mathematical Statistics: Theory, Applications, and Practice in R

Numéro d'article: 43464224

XAF 66043

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This book develops the theory of probability and mathematical statistics with the goal of analyzing real-world data.
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Ce qui se démarque

Comprehensive Coverage
Offers in-depth exploration of probability and statistical theory, alongside practical applications, making complex concepts accessible to students and professionals alike.
R Integration
Utilizes R for hands-on experience, allowing users to apply theoretical knowledge directly in a programming environment, enhancing learning and retention.
Problem Solving Focus
Emphasizes real-world problem-solving techniques, equipping readers with the skills to tackle statistical challenges in various fields, from academia to industry.

Détails du produit

Explore a wide range of Probability & Mathematical Statistics books with theory, applications, and practical examples in R at Ubuy Cameroon. Shop now for global delivery.
Publisher SIAM - Society for Industrial and Applied Mathematics
Publication date June 24, 2019
Language English
Print length 707 pages
ISBN-10 1611975778
ISBN-13 978-1611975772
Item Weight 3.6 pounds (1.63 kg)
Dimensions 1.89 x 7.28 x 10.35 inches (4.8 x 18.5 x 26.3 cm)

À qui est-ce destiné ?

Suitable For
  • Students of Statistics

    Ideal for undergraduate and graduate students seeking to understand probability and statistics with practical applications in R.

  • Data Scientists

    Useful for data scientists needing a solid foundation in statistical theory combined with practical tools for R programming.

  • Researchers

    Beneficial for researchers looking to apply statistical methods and analyses in their work using R software effectively.

Not Suitable For
  • Casual Learners

    Not suitable for casual learners seeking quick and simple introductions to probability or statistics without depth.

DESCRIPTION DU PRODUIT

Probability and Mathematical Statistics: Theory, Applications, and Practice in R

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Questions et réponses des clients

  • question: What programming language is used in the book?

    répondre: The book utilizes R programming language.
  • question: Who is the target audience?

    répondre: The book is written for use in applied masters classes, and is also suitable for advanced undergraduates and self-study by applied mathematicians, statisticians, and qualitatively inclined engineers and scientists.
  • question: What are the appendices about?

    répondre: The appendices include annotated solutions to 700 exercises and a Review of Useful Math.

Processes & Infrastructure Editorial Review

The editorial review of "Probability and Mathematical Statistics: Theory, Applications, and Practice in R" highlights the overall positive customer experience and reception of the textbook. Readers appreciate the clear and coherent organization of the material, making it accessible even for those who may find mathematical texts overly technical. Many students have found the book to be an invaluable resource, seamlessly supporting their learning during coursework, specifically in probability and mathematical statistics. Despite some critique about a lack of numerous examples, customers value the book’s approach, which allows them to quickly reference and understand specific concepts without getting bogged down in extensive proofs. The book's ability to serve as a reliable reference after completing formal studies speaks to its practical utility. Overall, this textbook seems to resonate well with its audience, providing a refreshing take on complex subjects. **

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Avantages

  • Clear and coherent flow of topics
  • Well-explained material that avoids overly technical jargon
  • Effective as a reference for refreshing concepts
  • Seamless support for coursework in probability and statistics

Les inconvénients

  • Limited examples provided

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