R programming

Author

Vijayakumar P

Published

Apr 18, 2026

Welcome

In an era where data drives decisions across every industry, the ability to work with data programmatically has become a foundational skill for students, researchers, and professionals alike. R, a free and open-source language built by statisticians for statisticians, has grown into one of the most widely used tools for data analysis, statistical computing, and visualization, and learning it opens the door to a vast ecosystem of packages and a thriving global community.

R Programming walks you through the language from the ground up, beginning with installation, the RStudio environment, basic syntax, variables, operators, and the core data types. From there, the book moves into R’s powerful data structures, vectors, lists, matrices, arrays, strings, data frames, and factors, and the operations that bring them to life, including manipulation with dplyr. The final chapters cover conditional statements, loops, and functions, equipping you with the building blocks needed to solve real problems through code.

Whether you are a student new to programming, an analyst moving into data science, or a researcher strengthening your computational toolkit, this book will acquaint you with the fundamentals of programming through R, the data structures available and operations performed on them, and the use of conditional logic and loops to build working programs. Each chapter is designed to move you steadily from understanding to application, so that by the end you can read, write, and reason about R code with confidence.

About the Authors

Vijayakumar P is an accomplished educator and data professional with over eight years of teaching and research experience in business analytics, data science, and HR analytics. He is a UGC Junior Research Fellow (JRF) and has qualified the UGC NET and SET in Management multiple times, reflecting his strong academic foundation.

Proficient in Python, R, STATA, SPSS, AMOS, PLS-SEM, Tableau, Power BI, Google Looker Studio, GitHub, and Excel , he has guided students and professionals in transforming data into actionable insights. His teaching spans business analytics using R and Python, HR metrics and dashboards, business forecasting, and business research methods, and he has also developed interactive eBooks to enhance hands-on learning.

Vijayakumar’s work is marked by clarity, precision, and innovation-whether in research, classroom teaching, or applied analytics-making data more accessible, impactful, and meaningful for decision-making.

References

  • R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. Wickham, H., & Grolemund, G. (2017). O’Reilly.
  • The Art of R Programming: A Tour of Statistical Software Design. Matloff, N. (2011). No Starch Press.
  • Advanced R. Wickham, H. (2019). (2nd ed.). Chapman and Hall/CRC.
  • R in Action: Data Analysis and Graphics with R. Kabacoff, R. I. (2015). (2nd ed.). Manning Publications.
  • Discovering Statistics Using R. Field, A., Miles, J., & Field, Z. (2012). SAGE Publications.
  • An Introduction to Statistical Learning: With Applications in R. James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). Springer.

Text Books

  • Hands-On Programming with R. Grolemund, G. (2nd ed.). O’Reilly.

Reference Books

  • R Programming for Beginners. Arora, S., & Malik, L. Universities Press.
  • The R Book. Crawley, M. J. Wiley.
  • Learning R. Cotton, R. O’Reilly.
  • R Programming for Beginners. Rakshit, S. McGraw Hill Education.