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Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10)
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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)
Item #: 30708971

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

85% of respondents would recommend this to a friend

Item #: 30708971

MYR 359

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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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What Stands Out

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.

Maklumat produk

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 Malaysia
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

Who Should Buy?

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.

PENERANGAN PRODUK

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

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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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Ulas Produk Ini

Kongsikan pandangan anda dengan pelanggan lain

Kebaikan

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

Keburukan

  • Not focused solely on statistics

Product Price History

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MYR 359

Pesan sekarang dan dapatkannya lebih kurang pada Sabtu, Oktober 31

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Ciri & Faedah

  • Learn practical and powerful tools of R for data analysis.
  • Hands-on approach with real-world examples and detailed commentary.
  • Covers standard regression methods and advanced topics.
  • Companion website with code and datasets for reproducibility.
  • Perfect for researchers, students of applied statistics, and practicing statisticians.
  • Expanded content on Bayesian inference, mixed models, and random forests.

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