Course Details in 2024/25 Session

Module Title	LM Statistical Modelling
School	Mathematics
Department	Mathematics
Module Code	06 40207
Module Lead	TBC
Level	Masters Level
Credits	20
Semester	Semester 1
Pre-requisites
Co-requisites
Restrictions	None
Contact Hours	Lecture-48 hours Guided independent study-152 hours Total: 200 hours
Exclusions
Description	This course is designed for students with limited or no prior finance or economic theory background. It emphasizes the understanding of quantitative methods, model evaluations, and the techniques for empirical studies including within finance and economics. This module will cover the basics and extension of ordinary least square methods, heteroscedasticity, autocorrelation, multicollinearity, model specifications, simultaneous equation models, binary and discrete choice models, qualitative and limited dependent variable models, time series analysis, panel data models, and nonparametric analysis with their applications including in finance and Economics. Students will gain hands-on experience formulating and estimating models, interpreting results, and making forecasts.
Learning Outcomes	By the end of the module students should be able to: Demonstrate an understanding of the nature of statistical inferential procedures involved in analysing data; Formulate models to solve some empirical problems; Apply appropriate statistical methods and techniques to understand relationships among variables; Use statistical computing programme of R; Demonstrate an understanding of the power and limitations of applied statistical analysis; Perform and present research by using relevant data and statistical tools; Demonstrate a comprehensive knowledge beyond the taught syllabus from personal exploration of the subject.
Assessment
Assessment Methods & Exceptions	Assessment: 80% examination, 20% coursework. Reassessment: Resit exam
Other
Reading List