View Specification DocumentStatistical Programming in R and Python (DD80) STATS3017
- Academic Session: 2026-27
- School: School of Mathematics and Statistics
- Credits: 20
- Level: Level 3 (SCQF level 9)
- Typically Offered: Runs Throughout Semesters 1 and 2
- Available to Visiting Students: No
- Collaborative Online International Learning: No
- Curriculum For Life: No
Short Description
The course develops students' skills in statistical programming, using the programming languages Python and R for programming and data analytics
Timetable
60 hours of practical sessions in computer labs.
Requirements of Entry
The normal requirement is that students should have been admitted to the third year of the Designated Degree programme in Statistics.
Excluded Courses
Statistical Programming [STATS4044]
Introduction to statistical programming in R and Python [STATS5103]
Co-requisites
The courses prescribed in the Designated Degree programme to which the student has been admitted.
Assessment
Programming Tasks (100%) consisting of in-lab and/or homework assessments.
Course Aims
To develop students' understanding of the key concepts and ideas of programming tools in the R and Python programming languages;
to provide computational skills which will support other Level 3 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 with appropriate control structures;
· make efficient use of the data structures built into R and Python;
· use R and Python to create informative and interpretable figures and graphs;
· describe and utilize features of classes and object-oriented design
· be aware of how to perform data-analytic tasks (e.g. using external libraries)