MT4113 Computing in Statistics

2024 to 2025 Semester 1

Curricular information may be subject to change

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

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 10

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

Not automatically available to General Degree students

Planned timetable

12.00 noon Mon (odd weeks) and Wed, 12.00 noon - 2.00 pm Fri

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

Module coordinator

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 description

The aim of this module is to teach computer programming skills, including principles of good programming practice, with an emphasis on statistical computing. Practical work focusses on the widely-used statistical language and environment R. Practical skills are developed through a series of computing exercises that include (1) modular programming; (2) manipulating data; (3) simulating data with specific statistical properties, (4) investigating behaviour of statistical procedures under failure of statistical assumptions.

Relationship to other modules

Pre-requisites

BEFORE TAKING THIS MODULE YOU MUST PASS MT2508 AND PASS MT3510

Anti-requisites

YOU CANNOT TAKE THIS MODULE IF YOU TAKE MT5763

Assessment pattern

3-hour Take-home Online Examination = 40% Coursework = 60%

Re-assessment

100% oral examination

Learning and teaching methods and delivery

Weekly contact

2.5 lectures (x 10 weeks), 1 x practical (x 10 weeks)

Scheduled learning hours

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

Guided independent study hours

115

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

Intended learning outcomes

Implement algorithms into computer code using modular programming in R
Write code that adheres to good programming practices
Implement key statistical and operations research algorithms
Code in a team using version control
Use computer software effectively to format data, produce graphics, improve code performance, and ensure reproducibility