Introduction to Statistical Computing and Visualization Using R
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Product details:
- Edition number 1
- Publisher CRC Press
- Date of Publication 20 July 2026
- ISBN 9781032788180
- Binding Paperback
- No. of pages408 pages
- Size 234x156 mm
- Weight 780 g
- Language English
- Illustrations 292 Illustrations, black & white 697
Categories
Short description:
The book provides a foundational guide to statistical computing and visualisation Using R programming with an emphasis on practical data analysis skills that are directly applicable to diverse fields like finance, defence, health, and education.
MoreLong description:
The book provides a foundational guide to statistical computing and visualisation Using R programming with an emphasis on practical data analysis skills that are directly applicable to diverse fields like finance, defence, health, and education. It uniquely combines a thorough explanation of basic constructs with advanced topics such as data visualisation, statistical modeling, and probability, making it accessible yet comprehensive for learners across disciplines. This approach allows readers not only to build essential R skills but also to apply them to real-world scenarios, equipping students and professionals from various disciplines with versatile analytical tools. It offers a comprehensive yet approachable introduction for students and scholars from various disciplines using R.
- Includes practical and interactive elements such as quizzes, coding exercises, and hands-on projects can provide an engaging and effective learning experience for readers
- Provides complete code solutions to every problem presented, including detailed answers to even the most complex questions
- Presents case studies that can help contextualize the concepts covered in the book by showing how they are used in specific industries, fields, or contexts
- Offers application-based practical data analysis with cases in various fields and sectors, such as finance, healthcare, and marketing
- Focuses on best practices and efficient coding techniques, improving productivity and maintainability of R code
Table of Contents:
1. Introduction to R 2. R Programming Concepts 3. Data Structures in R 4. String Handling in R 5. Data Import and Export 6. Data Visualization 7. Real-World Applications
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