Please note: there may be some adjustments to the teaching arrangements published in the course catalogue for 2020-21. Given current circumstances related to the Covid-19 pandemic it is anticipated that some usual arrangements for teaching on campus will be modified to ensure the safety and wellbeing of students and staff on campus; further adjustments may also be necessary, or beneficial, during the course of the academic year as national requirements relating to management of the pandemic are revised.

Introduction to R Programming (Level M) STATS5020

  • Academic Session: 2021-22
  • School: School of Mathematics and Statistics
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Either Semester 1 or Semester 2
  • Available to Visiting Students: No
  • Available to Erasmus Students: No

Short Description

The course introduces students to programming in the statistical software environment R.


10 2-hour practicals, and 10 hours of lectures.

Requirements of Entry

Some optional courses may be constrained by space and entry to these is not guaranteed unless you are in a programme for which this is a compulsory course..

Excluded Courses

STATS4044 Introduction to R Programming

STATS3017 Statistics 3R: Introduction to R Programming


Programming Tasks (100%) consisting of in-lab and homework assessments.

Course Aims

To introduce students to the basic concepts and ideas of a statistical computing environment; to train students in programming tools using the R computing environment; to provide computational skills which will support other M-level courses; and to introduce students to fundamental concepts in (scientific) programming in general.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ recognise and make appropriate use of different types of data structures;

■ use R to create sophisticated figures and graphs;

■ identify and implement appropriate control structures to solve a particular programming problem; and

■ design and write functions in R and implement simple iterative algorithms;

■ structure complex programming problems into functional units and implement these;

■ carry out extended programming tasks and produce clearly annotated listing of their code.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.