ST3131 Regression Analysis

Module Description
This module focuses on data analysis using multiple regression models. Topics include simple linear regression, multiple regression, model building and regression diagnostics. One and two factor analysis of variance, analysis of covariance, linear model as special case of generalized linear model. This module is targeted at students who are interested in Statistics and are able to meet the pre-requisites.

This is one of the most important core modules for a statistics major. Take it as soon as you can because it is the pre-requisite for many level 3000 modules. :)

Topics
- Introduction to regression
- Simple linear regression
- Multiple linear regression
- Introduction to generalized linear models

You will need to have basic knowledge of linear algebra and statistics for this module. The lecturer will use R during lecture as well as in tutorial, so you will need to remember ST2137.

Workload
Two two-hours lecture
This module was covered by Dr Yu Tao during my semester. Lecture notes are relatively straightforward but there are some difficult concepts. Dr Yu would go through a lot of proofs on the contents but I feel that these are mostly for understanding purposes. I can understand Dr Yu fairly well despite his chinese accent.

It was covered by Dr Chan Yiu Man in semester two of AY12/13. He introduced a project in this semester. I did not take ST3131 under him so I did not have to do the project.

Weekly one-hour tutorial
As usual, we have tutorials every single week. Homework are due every two weeks, so it's between doing them diligently or copying them from your friend. Every homework submission is counted to your CA. However, incomplete homework will be penalised.
Some of the tutorial questions require the use of R.

Textbook is recommended
Although it is not compulsory, I felt that the textbook helped a lot in clarifying my concepts.

Lectures were not webcasted

Assessment
10% Homework (Homework submission fortnightly)
10% Class Participation (Presentation of tutorial answers)
30% Midterm (True and false as well as open-ended)
50% Final (True and false as well as open-ended)
Cheatsheets are allowed for both midterm and final papers.

Extra notes to readers: I have the lecture notes. You can get all the files from my dropbox. Cheers!