Academic year(s): 2018-2019
SCOTCAT credits : 15
ECTS credits : 7
Level : SCQF Level 11
Availability restrictions: Not automatically available to General Degree students
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.
Pre-requisite(s): Undergraduates must pass MT4607 or MT5753 or MT5761
Anti-requisite(s): You cannot take this module if you take MT5757
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
As used by St Andrews: 2-hour Written Examination = 60%, Coursework = 40%
As defined by QAA
Written examinations : 60%
Practical examinations : 0%
Re-assessment: 2-hour Written Examination = 100%