Statistics Project STATS4050P

  • Academic Session: 2024-25
  • School: School of Mathematics and Statistics
  • Credits: 30
  • Level: Level 4 (SCQF level 10)
  • Typically Offered: Runs Throughout Semesters 1 and 2
  • Available to Visiting Students: No
  • Collaborative Online International Learning: No

Short Description

This project provides Single Honours students in Statistics with an opportunity to carry out an independent piece of data analysis, and to present their investigation in the form of a talk and a written report.

Timetable

None

Requirements of Entry

None

Assessment

Talk (10%)

Peer review (10%)

Project report (80%)

 

An Honours Project - no re-assessment available

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

The aims of this course are:

■ to give students experience of working independently to analyse an extensive dataset;

■ 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 data analysis;

■ describe the background to the project and the aims of the analysis;

■ formulate 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;

■ 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;

■ present the work of the project orally to an audience in a well-structured, precise and clear manner;

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

■ work independently, but with the support of an experienced supervisor available as required.

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.