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MT5764   Advanced Data Analysis

Academic year(s): 2018-2019

Key information

SCOTCAT credits : 15

ECTS credits : 7

Level : SCQF level 11

Semester: 2

Availability restrictions: Not automatically available to General Degree students

Planned timetable: Mon 12:00-1:00 Weeks 2, 4, 5, 8, 10 Tues, Thur 12:00-2:00, Weeks 1-10 (lectures) Tues 2:00 - 3:00 Weeks 2-9 (practicals)

This module covers modern modelling methods for situations where the data fails to meet the assumptions of common statistical models and simple remedies do not suffice. This represents a lot of real world data. Methods covered include: nonlinear models; basic splines and Generalised Additive Models; LASSO and the Elastic Net; models for non-independent errors and random effects. Pragmatic data imputation is covered with associated issues. Computer intensive inference is considered throughout. Practical applications build sought-after skills in R and the commercial packages SAS.

Relationship to other modules

Pre-requisite(s): Undergraduates must pass MT4607 or MT5753 or MT5761

Anti-requisite(s): You cannot take this module if you take MT5757

Learning and teaching methods and delivery

Weekly contact: 2.5 hours of lectures lectures (Weeks 1 - 10) and 8 practicals over the semester.

Scheduled learning hours: 33

Guided independent study hours: 116

Assessment pattern

As used by St Andrews: 2-hour Written Examination = 60%, Coursework = 40%

As defined by QAA
Written examinations : 60%
Practical examinations : 0%
Coursework: 40%

Re-assessment: 2-hour Written Examination = 100%


Module coordinator: Dr L A S Scott-Hayward
Module teaching staff: TBC