R Programming R Programming: R Data Analysis and Statistics, Book 2, (Paperback)
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R Programming R Programming: R Data Analysis and Statistics, Book 2, (Paperback)
R Programming: Data Analysis and Statistics is a beginner-friendly book that covers everything from the basics to more complex problems.
R Programming R Programming: R Data Analysis and Statistics, Book 2, (Paperback)
商品＃: 152162478

R Programming R Programming: R Data Analysis and Statistics, Book 2, (Paperback)

86% of respondents would recommend this to a friend

商品＃: 152162478

TWD 1118

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R Programming: Data Analysis and Statistics is a beginner-friendly book that covers everything from the basics to more complex problems.
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What Stands Out

Comprehensive Guide
Offers an in-depth exploration of R programming, covering essential data analysis techniques and statistical concepts suited for both beginners and advanced users.
Practical Examples
Incorporates real-world case studies and practical examples, helping readers apply R programming skills effectively for data analysis and interpretation.
User-Friendly Format
Designed in a paperback format for easy reading and reference, making it convenient for learners to explore R programming at their own pace.

產品詳情

Shop R Programming R Programming: R Data Analysis and Statistics, Book 2, (Paperback) online at a best price in Taiwan. 2642266671
Book formatPaperback
Fiction/nonfictionNon-Fiction
GenreComputing & Internet
Publication dateMay, 2023
Pages172
SubgenreProgramming
Series titleR Programming
Number in series2
Edition1
PublisherLadoo Publishing LLC
Original languagesEnglish
LanguageEnglish
Is collectibleN
Retail packagingSingle Piece
Assembled product height9 in
Assembled product weight0.52 lb (240 grams)
Bisac subject headingComputers

Who Should Buy?

Suitable For
  • Data Analysts

    Ideal for professionals looking to enhance their skills in data analysis using R programming effectively.

  • Students

    Great resource for university students studying statistics or data science who need a practical guide to R.

  • Beginner Programmers

    Perfect for beginners wanting to learn R, offering clear instructions and examples for foundational understanding.

Not Suitable For
  • Advanced Users

    Not suitable for experienced programmers who require in-depth or advanced programming techniques in R.

產品描述

R Programming R Programming: R Data Analysis and Statistics, Book 2, (Paperback)

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客戶問題與解答

  • 問題: Do I need prior knowledge of statistics to read this book?

    Answer: No, the book is designed for beginners and requires no prior statistical knowledge.
  • 問題: What topics are included in the book?

    Answer: The book includes R data manipulation, data visualization, supervised learning, and more.
  • 問題: Is this book suitable for advanced programmers as well?

    Answer: Yes, it also offers insights that can help advanced programmers expand their skills.

Andy Vickler All Books Editorial Review

R Programming: R Data Analysis and Statistics, Book 2, (Paperback) offers a comprehensive insight into the world of data analysis using R, making it an essential resource for anyone interested in computing and statistics. This non-fiction book contains 172 pages of valuable content published in May 2023 by Ladoo Publishing LLC. Readers will appreciate the structured approach to programming and data interpretation, along with its user-friendly layout that enhances learning. As part of the R Programming series, it caters to both beginners and intermediate users, fostering a deeper understanding of statistical concepts and their applications.

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優點

  • Comprehensive resource for data analysis
  • User-friendly layout for effective learning
  • Ideal for beginners and intermediates
  • Part of a structured programming series
  • Well-focused on practical applications

缺點

  • Limited to computing and programming topics

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特色和優勢

  • Beginner-friendly approach to statistical computing.
  • Covers basics and complex topics in R programming.
  • No prior statistical knowledge required.
  • Includes data manipulation and visualization techniques.
  • Ideal for both beginners and advanced programmers.
  • Learn to analyze large datasets effectively.

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