The document provides an overview of R programming, detailing its history, features, installation process, and comparisons with Java and Python. R is primarily used for statistical computing and data analysis, boasting extensive libraries and visualization capabilities. It also lists applications across various sectors and includes reference resources for further learning.

1. R Programming
Anjali Prajapati – 401
TYBSc (2022-23)

2. What Is R?
 Language For Statistical Computing.
 Statistical Techniques.
 Used by statisticians,
bioinformaticians & data miners.
 Visualization Capabilities.
 Highly Extensible.
 Cross Platform Compatible.

3. History
Features
How to install R?
Comparison between R, java & python
Applications
R Programming

4. History
Bells Lab
• 1976
Ross Ihaka &
Robert Gentleman
• 1991
Announcement
• 1993
GNU Public
Licence
• 1995
R Core Group
• 1997
Version 1.0.0
• 2000
Version 3.5.2
• 2019
Version 4.2.1
• 2022

5. Features
Features
Fast
Calculation
Large
Standard
Library
Extremely
compatible
Connects
with others
languages
2000+ free
libraries
Excellent
graphical
outputs
Vast
community

6. How to install R?
1.Go to the RStudio website.
1.Click on "DOWNLOAD" in the top-right corner.
1.Click on "DOWNLOAD" under the "RStudio Open
Source License".
1.Download RStudio Desktop recommended for your
computer.
1.Run the RStudio Executable file (.exe) for Windows
OS or the Apple Image Disk file (.dmg) for macOS X.

8. Comparison
R
• Statistical
modeling.
• More functions
and packages.
• Interpreter base
language.
• Mostly use for
data analysis.
Java
• Desktop GUI, web
servers.
• Large inbuilt
functions &
packages.
• Interpreter base
language.
• Used in design of
windows
application & web
application.
Python
• Web application
development.
• Less function
packages.
• Interpreter &
compiled base
language.
• Used in software
designing.

9. Applications
Banking Finance E-commerce Social Media Healthcare
Government Retail Insurance Electronics Manufacturing

10. Companies Using R

11. Reference Books & Links
1. R Programming by John
Hopkins University:
Coursera
2. Data Science R Basics
Certificate by Harvard
University: edX
3. R Training Course: Lynda
4. R Programming A - Z: R
for Data Science: Udemy
5. R Programming Course
and Tutorial Online:
Pluralsight