MT5766 Statistical Problem Solving

Academic year

2024 to 2025 Full Year

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

15

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.

Planned timetable

Lecture/Practical (Thursday 2pm)

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

Module coordinator

Dr H Worthington

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

Module Staff

Ben Swallow; Dr Fergus Chadwick; Dr Nicolò Margaritella

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

Module description

The module will focus on problem formulation and scientific reporting to different audiences. The module will consist of a set of case studies covering a range of application areas, for example, ecology, economics and medicine. The case studies will take the form of a key research question posed in a non-statistical way with an associated data set where appropriate. Students will be required to formulate the posed questions as a statistical problem and decide upon appropriate techniques to apply in each case. The coursework produced will be targeted at audiences ranging from readers of statistical journals to the general public. The form of the coursework will be different for each case study offering students the opportunity to improve their scientific writing and presentation skills. The module will also cover the importance of data protection and ethics approval alongside the promotion of science and statistics to wider audiences.

Relationship to other modules

Pre-requisites

BEFORE TAKING THIS MODULE YOU MUST PASS MT3507 OR PASS MT3508

Co-requisites

YOU MUST ALSO TAKE MT4113 OR TAKE MT5763

Assessment pattern

Coursework = 100%

Re-assessment

Coursework = 100%

Learning and teaching methods and delivery

Weekly contact

1 Lecture (x6 weeks), 1 practical (x16 weeks), 1 seminar (x2 weeks)

Intended learning outcomes

  • Formulate an appropriate statistical problem from a research question or dataset
  • Understand the different stages of the research process
  • Communicate statistics to different audiences in different formats
  • Understand and appreciate the importance of data protection and ethics
  • Use R as a tool for analysis and the visualisation of data and results