Kavi & Shila. R programming language For Beginners: Learn R Programming Language Tutorial

Kavi & Shila Book Publication House, 2024. — 226 p.Whether you're a student, researcher, or just someone curious about data, R programming can be your key to unlocking valuable insights. This book is designed to take you on a step-by-step journey from R novice to confident user.R is a programming language and software environment for statistical analysis, graphics representation, and reporting. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team. The core of R is an interpreted computer language that allows branching and looping as well as modular programming using functions. R allows integration with the procedures written in the C, C++, .Net, Python, or FORTRAN languages for efficiency. R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows, and Mac. R is free software distributed under a GNU-style copyleft and an official part of the GNU project called GNU S.R is a programming language and software environment for statistical analysis, graphics representation, and reporting. The following are the important features of R:
R is a well-developed, simple, and effective programming language that includes conditionals, loops, user-defined recursive functions, and input and output facilities.
R has an effective data handling and storage facility,
R provides a suite of operators for calculations on arrays, lists, vectors, and matrices.
R provides a large, coherent, and integrated collection of tools for data analysis.
R provides graphical facilities for data analysis and display either directly at the computer or by printing the papers.As a conclusion, R is the world's most widely used statistical programming language. It's the # 1 choice of data scientists and supis ported by a vibrant and talented community of contributors. R is taught in universities and deployed in mission-critical business applications. This tutorial will teach you R programming along with suitable examples in simple and easy steps.What You'll Learn:The Fundamentals: Grasp the core concepts of R, including data types, operators, control flow, and functions.
Data Manipulation: Master the art of wrangling data in R, from importing and cleaning to organizing and transforming it for analysis.
Statistical Powerhouse: Explore R's robust statistical capabilities, covering measures of central tendency, dispersion, hypothesis testing, and regression analysis.
Visualization Maestro: Craft compelling data visualizations with R's built-in graphics tools, bringing your data to life.
Practice Makes Perfect: Solidify your understanding with plenty of code examples, hands-on exercises, and practice problems throughout the book.
By the end of this journey, you'll be equipped to:
Tackle real-world data analysis projects.
Generate informative and impactful data visualizations.
Become an independent R programmer, ready to delve deeper into the world of Data Science.