MT5098 Group Dissertation for MSc Programme/s

Academic year

2024 to 2025 Full Year

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

60

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 11

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Availability restrictions

Available only to students enrolled on the MSc in Applied Statistics and Datamining

Planned timetable

To be arranged.

This information is given as indicative. Timetable may change at short notice depending on room availability.

Module coordinator

Dr B T Swallow

Dr B T Swallow
This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module Staff

Team Taught

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

This module is a group-based dissertation which is supervised by members of the teaching staff who will advise on the choice of subject and provide guidance and structure throughout the progress of the dissertation. This module results in an individually written and submitted dissertation of not more than 15,000 words. This dissertation may also include an agreed collaboratively written group report, but this report will constitute no more than 30% of the module grade. Each student is assessed taking into account both individual and group submissions.

Relationship to other modules

Pre-requisites

STUDENTS MUST BE ENROLLED ON THE MSC PROGRAMME IN THE APPLIED STATISTICS AND DATA MINING

Anti-requisites

YOU CANNOT TAKE THIS MODULE IF YOU TAKE MT5099

Assessment pattern

Dissertation = 100%

Re-assessment

no reassessment available

Learning and teaching methods and delivery

Weekly contact

1-hour supervision (x 13 weeks)

Scheduled learning hours

13

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

585

The number of hours that students are expected to invest in independent study over the period of the module.

Intended learning outcomes

  • Demonstrate a knowledge and understanding of an advanced area of applied statistics and datamining
  • Construct and evaluate logical arguments in the area of advanced study
  • Present information and research in the area of advanced study in an appropriate manner
  • Demonstrate skills in undertaking research as part of a team
  • Demonstrate competence in independent learning and time management