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Learning R: A Step-by-Step Function Guide to Data Analysis
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Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience.
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Ce qui se démarque
Détails du produit
| Publisher | O'Reilly Media |
| Publication date | October 22, 2013 |
| Edition | 1st |
| Language | English |
| Print length | 396 pages |
| ISBN-10 | 1449357105 |
| ISBN-13 | 978-1449357108 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 7 x 0.82 x 9.19 inches (17.8 x 2.1 x 23.3 cm) |
À qui est-ce destiné ?
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Beginner Analysts
Ideal for those starting with data analysis, offering clear guidance and practical examples using R programming.
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Students
Perfect for students in statistics or data science courses seeking to enhance their R skills through structured learning.
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Self-Learners
Great for individuals who prefer self-study, providing a step-by-step approach to mastering data analysis with R.
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Advanced Users
Not suitable for experienced data analysts seeking advanced techniques or complex statistical methods beyond basic R functions.
DESCRIPTION DU PRODUIT
Learning R: A Step-by-Step Function Guide to Data Analysis
Questions et réponses des clients
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question:
What is the primary focus of Learning R: A Step-by-Step Function Guide to Data Analysis?
répondre: The primary focus of this book is to provide a structured approach to learning R programming specifically for data analysis. It covers fundamental concepts, functions, and techniques used in R to manipulate, analyze, and visualize data effectively. This guide is particularly beneficial for beginners as it breaks down complex topics into digestible sections. -
question:
Who is the intended audience for this guide on Learning R?
répondre: This guide is suitable for individuals new to R programming as well as those with a basic understanding looking to enhance their data analysis skills. Data scientists, analysts, and students will find the step-by-step methodology particularly useful, allowing them to deepen their knowledge of R while applying practical examples relevant to their fields. -
question:
Can I use Learning R for statistical analysis projects?
répondre: Absolutely! Learning R is exceptionally valuable for statistical analysis projects. It introduces various functions and packages specifically designed for statistical computations. Whether you are performing regression analyses, hypothesis testing, or data summarization, the techniques covered in the guide will equip you with the skills needed for accurate data interpretation. -
question:
What kinds of data visualization techniques are covered in the book?
répondre: The book covers a range of data visualization techniques, including creating histograms, scatter plots, and box plots using R's ggplot2 package. These techniques help in interpreting data findings and presenting results visually, making it easier to convey insights to stakeholders, thus enhancing communication in data-driven decision-making scenarios. -
question:
Is prior programming knowledge required to understand this book?
répondre: No prior programming knowledge is required to understand Learning R. The guide is designed to accommodate beginners, starting with the basics of R syntax and gradually introducing more advanced concepts. This stepwise approach allows readers to build their programming skills incrementally, making it a friendly resource for newcomers to coding. -
question:
What unique features distinguish this R guide from others on the market?
répondre: This book distinguishes itself through its clear, concise explanations and a step-by-step format that caters specifically to data analysis using R. The practical examples provided help reinforce learning, while the focus on functions used in data analysis ensures that readers can apply their skills directly to real-world situations, enhancing their retention and usability of the language. -
question:
Does Learning R cover any case studies or practical applications?
répondre: Yes, Learning R includes various case studies and practical applications that illustrate how R can be used in real-world data scenarios. These examples allow readers to see the relevance of what they are learning and how to apply R in various fields, from healthcare to finance, making the information more relatable and applicable. -
question:
Can I use Learning R for machine learning applications?
répondre: While the primary focus of Learning R is data analysis, the skills and knowledge acquired can certainly be beneficial for machine learning applications. Understanding data manipulation and visualization is essential before diving into machine learning algorithms, making this guide a strong foundation for those looking to transition into that area. -
question:
How does Learning R approach the topic of data manipulation?
répondre: Learning R thoroughly explores data manipulation techniques using functions from libraries like dplyr and tidyr. These are essential for cleaning and transforming data efficiently, allowing users to prepare datasets for analysis. The book emphasizes practical application, ensuring that readers can manipulate their data seamlessly and focus on analytical tasks with confidence. -
question:
Where can I buy Learning R: A Step-by-Step Function Guide to Data Analysis 1st Edition?
répondre: You can buy Learning R: A Step-by-Step Function Guide to Data Analysis 1st Edition on Ubuy. It is a reliable platform where you can find various editions of this book and have your choice delivered to your doorstep.
Software Development Editorial Review
The O'Reilly book on R programming seems to be getting mixed reactions from customers. While some say it arrived on time and in great condition, others found the book terribly written with half-baked information. The subject can be difficult to grasp if you don't have a programming background, as concepts, terminology, math-involved, etc. are all poorly defined, according to some reviews. However, a few customers believe that the book is classical and useful, and it even includes chapters at the end on writing your packages. The book serves as a decent introduction to R for beginners, but some people believe that they would have to buy an additional book for more detailed information.
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Avantages
- Arrived on time and in great condition.
- A fantastic introduction to R programming.
Les inconvénients
- Terribly written book with half-baked information.
CONFIANCE EN LA PLATEFORME & PROTECTION DE L'ACHETEUR
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Caractéristiques et avantages
- Step-by-step guide to learning R for data analysis
- Suitable for beginners with little or no programming experience
- Covers essential R tools for data analysis
- Real data analysis examples included
- Includes quizzes and exercises to reinforce learning
- Learn how to clean data, visualize and summarize statistics, and make predictions
Assurance Ubuy
Profitez d'une expérience d'achat sereine avec des produits 100 % originaux, une sécurité de paiement conforme PCI DSS, une protection des données certifiée ISO 27001, la livraison transfrontalière la plus rapide, les retours gratuits* et un emballage sécurisé pour chaque commande.