Statistics BSc/MSci

Professional Skills STATS4048

  • Academic Session: 2023-24
  • School: School of Mathematics and Statistics
  • Credits: 10
  • Level: Level 4 (SCQF level 10)
  • Typically Offered: Either Semester 1 or Semester 2
  • Available to Visiting Students: No

Short Description

A practical, lab-based course which delivers experience in the key skills needed by the professional statistician; communication and presentation of results from a statistical analysis.


Practical: 5, two-hour data-analysis sessions (alternate weeks)

Workshop: 5 two-hour sessions (alternate weeks)

Excluded Courses

STATS5023  Professional Skills (Level M)


Laboratory work (100%)

Main Assessment In: April/May

Are reassessment opportunities available for all summative assessments? Not applicable

Reassessments are normally available for all courses, except those which contribute to the Honours classification. For non Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

Course Aims

To prepare students for their possible future role as practising statisticians;

to develop general expertise in formulating statistical approaches to practical problems in a wide variety of subject areas;

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

to provide the opportunity for active and independent learning.

Intended Learning Outcomes of Course

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

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

■ critically collate results and conclusions;

■ interpret the output of R procedures.

■ Use basic features an appreciation of word-processing and presentation software;

■ work actively and independently, as well in teamwork on practical data analysis;

■ explain results and conclusions to the client;

■ develop experience and expertise in presenting the results of analyses both orally, to an audience, and in the form of written reports.

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.