Principles of Regression Analysis

Synopsis

MTH307 is the first of two sequential courses on applied regression anlysis (the second one is MTH308: Applications of Regression Analysis). It aims to lay the theoretical foundation essential to regression analyis. Topics include review on probability & statistics, simple linear regression, and multiple linear regression.

Level: 3
Credit Units: 5
Presentation Pattern: Every January

Topics

Introduction and review of probability & statistics.
Sampling distributions and the Central Limit Theorem.
Testing a hypothesis about a population mean.
Overview of regression analysis.
Simple linear regression.
Model assumptions.
The coefficient of correlation.
Using the model for estimation and prediction.
General form of a multiple regression model.
A first-order model with quantitative predictors.
The multiple coefficient of determination, R-squared.
Testing the utility of the model: the analysis of variance F Test.

Learning Outcome

Implement linear and multi linear regression models.
Determine linear unbiased properties of regression models.
Determine mean and variance of and between regression model parameters.
Interpret test statistics of regression model parameters.
Analyze multiple regression models.
Interpret regression model parameters from data.

Part-time Programmes / CET Courses

Singapore University of Social Sciences

Principles of Regression Analysis

Principles of Regression Analysis (MTH307)

Synopsis

Topics

Learning Outcome