3 Introduction of R and R studio

3.1 Getting Started

• You can use R/R studio in the PC room.
• However, I strongly recommend you install R/Studio in your laptop and bring it to the class.
• Install in the following order
  1. R: https://www.r-project.org/
  2. Rstudio: https://www.rstudio.com/
• Now open Rstudio.

3.2 Helps

• The RStudio team has developed a number of “cheatsheets” for working with both R and RStudio.
• This particular cheatsheet for Base R will summarize many of the concepts in this document.

3.3 Quick tour of Rstudio

• There are four panels
  1. Source: Write your own code here.
  2. Console:
  3. Environment/History:
  4. Files/Plots/Packages/Help:
• In the Source panel,
  • Write your own code.
  • Save your code in .R file
  • Click Run command to run your entire code.
• In the concole panel,
  • After clicking Run in the source panel, your code is evaluated.
  • You can directly type your code here to implement.

3.4 Basic Calculations

To get started, we’ll use R like a simple calculator.

Addition, Subtraction, Multiplication and Division

Math	R	Result
\(3 + 2\)	3 + 2	5
\(3 - 2\)	3 - 2	1
\(3 \cdot2\)	3 * 2	6
\(3 / 2\)	3 / 2	1.5

Exponents

Math	R	Result
\(3^2\)	3 ^ 2	9
\(2^{(-3)}\)	2 ^ (-3)	0.125
\(100^{1/2}\)	100 ^ (1 / 2)	10
\(\sqrt{100}\)	sqrt(100)	10

Mathematical Constants

Math	R	Result
\(\pi\)	pi	3.1415927
\(e\)	exp(1)	2.7182818

Logarithms

• Note that we will use \(\ln\) and \(\log\) interchangeably to mean the natural logarithm.
• There is no ln() in R, instead it uses log() to mean the natural logarithm.

Math	R	Result
\(\log(e)\)	log(exp(1))	1
\(\log_{10}(1000)\)	log10(1000)	3
\(\log_{2}(8)\)	log2(8)	3
\(\log_{4}(16)\)	log(16, base = 4)	2

Trigonometry

Math	R	Result
\(\sin(\pi / 2)\)	sin(pi / 2)	1
\(\cos(0)\)	cos(0)	1

3.5 Getting Help

• In using R as a calculator, we have seen a number of functions: sqrt(), exp(), log() and sin().
• To get documentation about a function in R, simply put a question mark in front of the function name and RStudio will display the documentation, for example:

?log
?sin
?paste
?lm

3.6 Installing Packages

• One of the main strengths of R as an open-source project is its package system.
• To install a package, use the install.packages() function.
  • Think of this as buying a recipe book from the store, bringing it home, and putting it on your shelf.

install.packages("ggplot2")

• Once a package is installed, it must be loaded into your current R session before being used.
  • Think of this as taking the book off of the shelf and opening it up to read.

library(ggplot2)

• Once you close R, all the packages are closed and put back on the imaginary shelf.
• The next time you open R, you do not have to install the package again, but you do have to load any packages you intend to use by invoking library().