Book Details

Implementing R for Statistics is a timely first edition textbook that provides comprehensive coverage of basic statistical concepts using R, an important open-source programming language tool. This book guides the readers through understanding the R basics, from installing R and RStudio to exploring its basic structure and uses, to implementing and practicing these in statistics. Using the sophisticated and elegant data visualization of R, this book explains the latest advances in the R programming language using illustrated examples carefully designed to apply the core principles discussed in the text to emerging topics in the field. It also provides useful insights into the process of developing R packages and creating metadata, focusing on exploiting the flexible and user-friendly nature of R. Written by an international and experienced team of authors, Implementing R for Statistics is an essential text for students, lecturers, data scientists, and applied researchers in all areas of statistics and related fields such as biostatistics, health care, finance, risk management, social sciences, market research, and environmental and climate research.

Key Features

• Introduces core statistics concepts and their application using R in an accessible manner
• Explains the newest advances in implementing R in statistics through clear and highly illustrated examples
• Explores the process of learning R from installation to package creation
• Covers important and evolving aspects of R, such as using RStudio, metadata management, and advanced regression modeling techniques
• Includes references to the latest R packages, demonstrating up-to-date tools available in the field