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Hands-On Programming with R: Write Your Own Functions and Simulations 1st Edition
80% of respondents would recommend this to a friend
RON 208
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Learn how to program by diving into the R language, and then use your newfound skills to solve practical data science problems
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Product Details
| Item Weight | 1.2 lbs (540 grams) |
Who Should Buy?
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Beginners in R
Perfect for those new to R, providing clear examples for learning programming fundamentals and R syntax.
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Data Science Students
Ideal for students studying data science who need hands-on experience in programming with R and creating simulations.
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Self-learners
Great for self-motivated learners seeking practical experience with R through exercises and real-world applications.
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Experienced Programmers
Not ideal for seasoned programmers, as it covers basic concepts rather than advanced programming techniques.
Product Description
Hands-On Programming with R: Write Your Own Functions and Simulations 1st Edition
Customer Questions & Answers
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Question:
Is this book for beginners or advanced programmers?
Answer: This book is designed for beginners who want to learn programming with R. However, it can also be useful for advanced programmers who want to expand their knowledge of R programming tools. -
Question:
Does the book include exercises to practice programming?
Answer: Yes, the book includes exercises that you can use to practice programming concepts as you learn them. -
Question:
Do I need to have experience in data science to read this book?
Answer: No, you don't need any prior experience in data science to read this book. It's designed to teach you programming with R from scratch.
Probability & Statistics Editorial Review
**** "Hands-On Programming with R: Write Your Own Functions and Simulations" by Garrett Gromlemund has emerged as a standout guide for those venturing into the R programming language, particularly for individuals who might be daunted by its initial complexities. Readers have expressed that the book not only provides a solid foundation in essential programming Constructs such as vectors, matrices, lists, and data frames, but also effectively clarifies how these data structures interconnect. One notable strength of the book is its engaging approach; Gromlemund combines practical exercises with a touch of humor, making learning R more enjoyable compared to traditional textbooks. Reviewers appreciate the author's attention to detail and the practical examples, such as using a deck of cards to explain data frames, which they found helpful and relatable. The programming section, where Gromlemund delves into the design and implementation of functions and simulations, is particularly well-received and is likely to resonate with readers eager to develop their coding skills. However, some criticisms were raised regarding the book's length relative to its price and a perceived lack of thorough proofreading. The chapter on environments, while potentially interesting, was perceived as complex, especially for newcomers to programming, suggesting that it may not cater well to absolute beginners. Despite these drawbacks, many readers assert that this book is a valuable resource for understanding R and prefer it over online tutorials. It has been recommended as a foundational text for those looking to build their R programming skills, ideally paired with another introductory book for a more rounded approach. Overall, customer experience with "Hands-On Programming with R" is overwhelmingly positive, with many readers noting that it has significantly aided their understanding and application of R, especially for statistical programming and simulations. **
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Pros
- Clear explanations of R data structures (vectors, matrices, lists, data frames).
- Engaging writing style with humor, making learning enjoyable.
- Effective practical examples and exercises throughout.
- Strong focus on foundational programming concepts.
- Highly recommended for beginners in R programming.
Cons
- Expensive for its size (200 pages + appendices).
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RON 208
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Features & Benefits
- Master the programming language of R
- Solve practical data science problems
- Learn R programming tools and debugging
- Work hands-on with 3 data analysis projects
- Write your own functions and simulations
- Store, retrieve, and change data values in your memory
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