Introduction to statistical programming in R and Python STATS5103

  • Academic Session: 2023-24
  • School: School of Mathematics and Statistics
  • Credits: 20
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Either Semester 1 or Semester 2
  • Available to Visiting Students: No

Short Description

The course introduces students to statistical programming, the programming languages R and Python and their use for data programming and analytics.



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


100% continuous assessment:

This will typically be made up of 4 assessments (e.g. timed class tests or take-home assessments worth 25% each).

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 and Python computing environments; 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:

■ design and implement functions in R and Python;

■ make efficient use of the data structures built into R and Python;

■ use R and Python to create informative and interpretable figures and graphs;

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

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

■ describe and exploit features of classes and object-oriented design

■ implement data-analytic tasks (e.g. using external libraries such as scikit-learn, NumPy/SciPy and pandas)

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.