Postgraduate Course: MIGSAA Statistics 1 (MATH12019)

Course Outline
School	School of Mathematics	College	College of Science and Engineering
Credit level (Normal year taken)	SCQF Level 12 (Postgraduate)	Availability	Not available to visiting students
SCQF Credits	15	ECTS Credits	7.5
Summary	One aim is to introduce some key topics which lie at the heart of research in statistical methods and form a basis for more advanced and sophisticated ideas. Another is to develop good computational skills using R, the statistical computing package which is in widespread use for statistical work in academia and industry.
Course description	- Introduction to R - Review of linear models - Likelihood methods (and optimisation) - Review of generalised linear models - Simulation and bootstrapping - Case study

Entry Requirements (not applicable to Visiting Students)
Pre-requisites		Co-requisites
Prohibited Combinations		Other requirements	None

Course Delivery Information

Academic year 2022/23, Not available to visiting students (SS1)		Quota: None
Course Start	Semester 1
Timetable	Timetable
Learning and Teaching activities (Further Info)	Total Hours: 150 ( Lecture Hours 20, Programme Level Learning and Teaching Hours 3, Directed Learning and Independent Learning Hours 127 )
Assessment (Further Info)	Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment)	Coursework : 100%
Feedback	Not entered
No Exam Information

Learning Outcomes
Gain an introductory understanding of some key topics which lie at the heart of research in statistical methods and form a basis for more advanced and sophisticated ideas.