This PDF covers Introduction and
preliminaries, Simple manipulations : numbers and vectors, Objects, Ordered and
unordered factors, Arrays and matrices, Lists and data frame, Reading data from
files, Probability distribution, Grouping, Statistical models in R, Graphical
procedures, Packages, OS Facilities, Invoking R, The command-line editor,
function and variable index.
This book covers the history and fundamentals of R,
guiding readers through installation and usage of R, R Studio, and R Shiny.
Explore data manipulation, interfaces, and visualization, while mastering
statistical modeling and machine learning. Real-world case studies offer
practical insights into hypothesis generation, data exploration, and model
building. This guide is your essential companion for mastering statistical
computing and data science using R.
Author(s): Sathyabama Institute of Science and Technolog
This PDF covers the following
topics related to R Programming : Introduction, Basic Arithmetic and Objects ,
Data, Functions, Graphics, The apply Family of Functions, Arrays and Tables,
Strings, Classes and Methods, Debugging, Arithmetic Subtleties, List of the Most
Useful Functions in R.