Introduction to R

This is a one day intensive course on basics and fundamental concepts of R. The course is structured as a set of lecture sessions and computer practicals. It is suitable to a wide range of participants e.g., statisticians, biologists, clinicians and postgraduate students.

The course assumes no prior programming skills.


  • What is R?: A brief overview of the concepts and features of the R statistical programming environment.
  • Help systems in R: A description of how to use different sources of R help.
  • Data types: A brief introduction to different data types in R including numeric, complex, character, factor and logical data.
  • Data structure: A summary of R’s data structure including vectors, matrices, arrays, data frames and lists.
  • Importing data: Describing how to import, edit, save and export data of different formats from R including Excel, SPSS, STATA and SAS data files.
  • Data manipulation: A description of how to use logical operators to manipulate data.
  • Missing values: Describing how R handles missing values.
  • Visualisation: Creating, editing and saving graphics in various formats using R.


Dr. Osama Mahmoud, Lecturer in Data Science and Statistics, the Director of UG and PG Data Science programmes at the Department of Mathematical Sciences, University of Essex, UK.


The course slides, R scripts, practical questionas and answers covered in this course can be found on my statcourses github page.


Each course is associated with an R package tailored to combine together the practical sheets with solutions, course notes and training data sets. The R package associated with this course, named 'dsEssex', can be simply installed by running the following code lines into your R session.

# required only once per machine!
if(!require("devtools")) install.packages("devtools")

The package can then be loaded via: