Year of Study:	2
Credit Units:	3
Duration:	45hours
Prerequisites:	AMS1001 Introduction to Linear Algebra and Calculus and AMS1302 Probability and Statistical Theory; or with the Instructor’s permission and upon endorsement of the relevant Chairperson or Programme Director.

This module aims to provide students with an understanding of the classical and
modern regression analysis and techniques which are widely adopted in various
areas such as business and finance. Students can apply modern regression
techniques to analyse multivariate business data and solve real-world business
problems with/without the use of state-of-the-art statistical packages. Students are
also required to present their findings to their peers and professors in a
professional manner.

Upon completion of this module, students should be able to:

1. understand and apply matrix algebra and different distributions used in regression analysis;


2. apply statistical inference for linear and multiple regression models;


3. conduct model selection, perform model diagnostics, and understand the basic concepts of non-linear regression analysis; and


4. apply regression techniques with/without the use of computer software to interpret and present the results in a scientific and concise manner, and work effectively in a team and solve problems logically, analytically, critically and independently.