Introduction to Biostatistics
Shamik Sen
Dept. of Biosciences & Bioengineering
IIT Bombay
What is R?
• Software environment for statistical computing and data
analysis
• R is a GNU package and source code of R is freely available.
• Pre-compiled binary versions are provided for various
operating systems.
• R has a command line interface. But many graphical user
interfaces are available.
• R can produce publication-quality graphs with
mathematical symbols
R is an interpreted language
Applications of R
• Mainly used by statisticians and other practitioners
requiring an environment for statistical computation and
software development.
• R supports matrix arithmetic and can also operate as a
general matrix calculation toolbox – with performance
benchmarks comparable to GNU Octave or MATLAB
• R can be used to perform high-performance statistical
computation required for statistical analysis of Big Data.
• R is also being used in Business Analytics.
Getting R - 1
• R is an open source programming language. Due
to its popularity pre-compiled R binaries are also
available for different platforms.
• Binaries for windows, Unix or MacOS can be
downloaded from R project website
https://www.r-project.org.
• These binaries can directly be used to install the R
programming of a computer.
Getting R - 2
• However, R is command line so may not be
suitable for learners.
• For this, many graphical under interfaces
(GUIs) software are available for R.
• These GUIs-based software provide an user
friendly interface to write, correct and run R
code.
• Rstudio is one such widely used GUI interface
for R.
Getting R - 3
• RStudio
workspace
Command
windows
Additional
information
Creating vectors in R
Creating vectors in R
Basic operations on vectors - 1
Basic operations on vectors - 1
Importing data to R - 1
CSV: comma separated values
.xlsx format
.csv format
Importing CSV data to R
Workspace
Calculating descriptive statistics in R-1
Finding frequency in categorical data
Mean, median, min & max
Calculating descriptive statistics in R-2
Variance and standard deviation
Alternatively
Calculating descriptive statistics in R-3
Querying
Sorting
Which()
Summary()
Plotting in R - 1
Plotting in R - 2
