Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10)
Discover what you can do with R! This book guides users through practical, powerful tools for hands-on analysis and interpretation of data.
Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10)
Numéro d'article: 30708971

Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10)

Numéro d'article: 30708971

DZD 10237

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Discover what you can do with R! This book guides users through practical, powerful tools for hands-on analysis and interpretation of data.
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Ce qui se démarque

Example-Based Learning
Offers practical, example-driven learning that makes complex concepts accessible, enhancing understanding and retention for students and professionals alike.
Comprehensive Coverage
Thoroughly covers data analysis techniques and graphics using R, equipping readers with essential skills needed for real-world data scenarios and problem-solving.
Updated Content
Includes the latest advancements in R and statistical methods, ensuring readers stay current in the rapidly evolving field of data science.

Détails du produit

Explore the Example-Based Approach of Data Analysis and Graphics Using R. Discover how to apply statistical and probabilistic mathematics through Cambridge Series Number 10. Shop at Ubuy Algeria
Publisher Cambridge University Press
Publication date June 7, 2010
Edition 3rd
Language English
Print length 549 pages
ISBN-10 0521762936
ISBN-13 978-0521762939
Item Weight 2.87 pounds (1.3 kg)
Dimensions 7.25 x 1.25 x 10 inches (18.4 x 3.2 x 25.4 cm)
Part of series Cambridge Series in Statistical and Probabilistic Mathematics

À qui est-ce destiné ?

Suitable For
  • Students and Learners

    Perfect for students aiming to solidify their understanding of data analysis using R through practical examples.

  • Data Analysts

    Ideal for professionals who need to enhance their data visualization skills and apply statistical techniques effectively.

  • Teachers and Educators

    Beneficial for educators looking for comprehensive teaching materials and examples to guide students in data analysis.

Not Suitable For
  • Complete Beginners

    Not suitable for individuals with no prior experience in R or data analysis concepts, as it assumes some knowledge.

DESCRIPTION DU PRODUIT

Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10)

Vous avez une question ? Chattez avec nous

Questions et réponses des clients

  • question: Who is this book ideal for?

    répondre: It's ideal for research scientists, final-year undergraduate or graduate-level students of applied statistics, and practicing statisticians.
  • question: Does the book require prior knowledge of R?

    répondre: No, it assumes basic statistical knowledge and some experience with data analysis, but not prior experience with R.
  • question: What additional resources come with the book?

    répondre: A companion website offers code, datasets, and solutions to selected exercises to enhance learning and reproducibility.
  • question: Is this book helpful for learning R?

    répondre: Yes, this book is very useful for learning R and provides code examples and highlights common pitfalls for new users.

Biostatistics Editorial Review

This book is highly recommended for anyone looking to learn R and statistics. It provides useful code examples and highlights common pitfalls for new users. The included website allows for easy access to downloadable code. While there are free resources available, this hard-bound reference book offers a comprehensive and organized approach to learning R. It covers a range of statistical applications and provides value even if only a few chapters are utilized.

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Avantages

  • Useful for learning R
  • Includes code examples
  • Highlights common pitfalls
  • Comprehensive reference
  • Covers range of statistical applications

Les inconvénients

  • Not focused solely on statistics

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