 Название: Introduction to Statistical Computing and Visualization Using R
Автор: Megha Rathi
Издательство: CRC Press
Год: 2025
Страниц: 420
Язык: английский
Формат: epub (true)
Размер: 10.1 MB
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.
In this book, you will learn the basics of R programming, including data types, functions, control structures, data structures, functions, and many more. A step-by-step procedure to install and set up R on various operating systems, as well as information on the integrated development environment (IDE) used for writing R code, is provided in this book. You will also gain an understanding of statistical concepts like central tendency measures, evaluation metrics, etc. This book includes information on how to use R for string handling and pattern recognition. The ability to handle strings and recognize patterns is crucial in data analysis and computational fields, as it facilitates the extraction, manipulation, and processing of textual data. The ability to handle strings and recognize patterns is crucial in data analysis and computational fields, as it facilitates the extraction, manipulation, and processing of textual data. This book includes numerous real-world examples and practice exercises to help reinforce your learning. Whether you are looking to enhance your data analysis skills, improve your understanding of statistics, or simply learn a new programming language, this book will provide you with a strong foundation in R programming and its practical applications.
The book provides guidance on programming best practices, including code organization, debugging techniques, and version control. This book enriches readers with a solid foundation in R programming and statistical analysis, preparing them for further learning and exploration.
Examples of real-world applications of R are included in the book, demonstrating how the language can be used to address problems in diverse fields like finance, healthcare, and social sciences. Complete details are provided to readers on utilizing R’s visualization libraries to generate informative and impactful visualizations. It encompasses data manipulation techniques such as subsetting, merging, reshaping, and summarizing data frames.
R programming language is a powerful and flexible tool for data analysis and statistical computing. R aims to make complex statistical analysis accessible to a wide range of users, from beginners to experts, by providing a comprehensive set of built-in functions and libraries.
R is also designed to be extensible, allowing users to create their own functions and libraries to address specific analytical needs. Additionally, R is an open-source language, which means that it is free to use and modify, and has a vibrant community of developers and users who contribute to its ongoing development and improvement. Overall, the objective of R is to enable users to analyse, visualize, and model data efficiently and effectively, in a way that is accessible to both experts and novices.
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
Contents:
1.Preface
2.Author Biography
3.Introduction
4.1. Introduction to R
5.2. R Programming Concepts
6.3. Data Structures in R
7.4. String Handling in R
8.5. Data Import and Export
9.6. Data Visualization
10.7. Real-World Applications
11.Answer Keys
12.Index
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Introduction to Statistical Computing and Visualization Using R 
