Postgraduate study

Postgraduate taught 

Advanced Statistics MSc

Advanced Statistics Project and Dissertation STATS5091P

  • Academic Session: 2026-27
  • School: School of Mathematics and Statistics
  • Credits: 60
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Summer
  • Available to Visiting Students: No
  • Collaborative Online International Learning: No
  • Curriculum For Life: No

Short Description

This project provides Masters-level students in Statistics with an opportunity to carry out an independent piece of statistical analysis, and to present their investigation in the form of a dissertation.

Timetable

Supervisory meetings to be arranged throughout the summer semester (15 hours total), with additional writing and presentation skills seminars throughout the year (20 hours total).

Excluded Courses

Statistics Project and Dissertation (STATS5029P)

Statistics Project and Dissertation with Placement (STATS5090P)

Assessment

Interim assessment (20%, including a presentation and mini-viva) + dissertation (80%).

Course Aims

The aims of this course are:

■ to give students experience of working independently on an advanced piece of statistical analysis, including developing new statistical methodology as appropriate;

■ to develop written and verbal presentation and communication skills.

Intended Learning Outcomes of Course

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

■ integrate the knowledge and skills they have gained from other components of their degree programme in order to carry out an extended piece of statistical analysis;

■ investigate and describe in detail the background to the project;

■ formulate the aims of the analysis and specific questions of interest in appropriate technical and non-technical language;

■ explain the role of statistics in answering the questions of interest;

■ identify relevant statistical methodology, if necessary including methods not formally introduced in other components of their degree programme;

■ formulate an appropriate analysis plan, and update it as required;

■ implement their chosen methods using statistical packages and programming as required;

■ check the validity of the assumptions underpinning their chosen methods;

■ interpret the results and write appropriate conclusions in technical and non-technical language;

■ explain clearly the implications and limitations of the analysis;

■ defend their analyses and conclusions in a mini-viva;

■ present the work of the project in the form of a written report in a well-structured, precise and clear manner.

Minimum Requirement for Award of Credits

No exceptions