Postgraduate taught 

Statistics MSc

Data Analysis Skills (Level M) STATS5085

  • Academic Session: 2023-24
  • School: School of Mathematics and Statistics
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No

Short Description

This course gives students the experience of analysing data in a wide variety of contexts, using the R computer package, develops written and verbal communication skills, and provides an opportunity for students to carry out a short data-sourcing and analysis project. The practical, lab-based course delivers experience in key skills needed by the professional statistician.


10 2-hour labs

14 additional hours of lectures and workshops

Excluded Courses

STATS4048 Professional Skills

STATS4052 Data Analysis

STATS3011 Statistics 3A: Data Analysis


Practical skills assessment (100%) of independent and group work on statistical analysis tasks, typically including quizzes (25%), in-class tests (50%), and a group project and presentation (25%).

Course Aims

This course aims to prepare students for their possible future role as practising statisticians, by

■ learning to work independently in statistical planning, implementation, and data analysis;

■ critically integrating the knowledge acquired in the other courses taught in this programme;

■ developing written and verbal skills of presentation and communication, through case studies, teamwork exercises and associated written reports and presentations;

■ introducing students to the social, ethical, legal, and professional issues arising in Statistical research.

Intended Learning Outcomes of Course

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

■ work independently, as well as in a team, on practical data analysis tasks;

■ perform the steps in completing a formal statistical analysis, including visualization, data wrangling, identifying relevant statistical methodology, its implementation and validation;

■ develop an analysis plan and implement an appropriate modelling strategy to answer questions of interest about a given data set;

■ implement the statistical techniques covered in other postgraduate courses in R;

■ use features of scientific word-processing and presentation software, including the creation of reproducible documents in R;

■ critically collate the results from statistical procedures, interpret them, draw appropriate conclusions and write up the results clearly as a report;

■ communicate conclusions from data analyses effectively in a presentation;

■ develop, present and critically reflect upon arguments on social, ethical, legal and professional issues in Statistics.

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.