Basics of R
Duration 3-4 hours
Training Points 1.0
Team Researcher Academy

This course is delivered by the Researcher Academy

Researcher Academy courses are very popular and the majority are run in both semesters to give you the opportunity to attend at a time of the year that suits you. Semester 1 courses will be available for booking from the second week of October and Semester 2 courses from the second week of February.

Unfortunately this course will not run in 2020/21 due to Cov-19 restrictions. However, the course materials which accompanied this course have been made available on Moodle for self-study. There are no training points or attendance certificate available for completing the self-study exercises. 
Introduction to R resource page on Moodle.

Postgraduate research students and Research-only staff (ECRs) in the Faculty of Medicine and Health Sciences (M&HS) only. 

In classroom only. Lectures and Computer-based practical workshop.

Learning outcomes

  • Become familiar with R programming environment and basic functions of R
  • Know how to deal with different types of data
  • Know how to use R to do basic descriptive analysis and graphical presentations
  • Know how to perform basic statistical tests and interpret the results

Course Description

R is a free, popular language and environment that allows powerful and fast manipulation of data, offering many statistical and graphical options. This course is recommended for those who want to learn the basics of R programming. It aims to introduce R as a tool for statistics and graphics, with the main aim being to become comfortable with the R environment. It will focus on entering and manipulating data in R and producing graphs. Basic statistics will be briefly introduced, important and useful statistical functions will be covered in detail. Lecture will be interactive with a focus on learning by example. No prior programming experience is needed.

This course includes the following topics:

  1. Introduction to the R platform and interface
  2. Dealing with various data objects such as vector, matrix and data frame
  3. R Environment
  4. Statistics in R
  5. R Graphics

Booking Conditions

Latecomer policy

Researchers should plan to arrive prior to the advertised course start time. Except for exceptional reasons, there will be no admittance to a Researcher Academy or Faculty Training Programme (FTP) course 15 minutes after the advertised course start time.

Importance of booking commitment

When booking on to a Researcher Academy short course you are entering into a commitment to attend. If you find that you are no longer available to attend you MUST cancel your place (on the system if more than three days before the course) or if at short notice by emailing This will ensure that your place can be offered to another researcher on the waiting list. Failure to cancel a place results in other researchers missing out on places through the waiting list process.

It is unacceptable for researchers to just not attend when booked onto a course. Researcher Academy maintains records of those who repeatedly do not attend courses they have booked. This may affect future eligibility to book onto further Researcher Academy courses and will affect considerations for Researcher Academy funded opportunities.

Pre-Requisites Pre-requisites: Good working knowledge of basic statistics and computing is highly desirable, but no prior programming experience is needed.
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