Statistical Model Building

Course Purpose

To enable the learner to construct mathematical description of some real-world phenomena that accounts for the uncertainty and/or randomness involved in that system.

Learning Outcomes

By the end of the course the learner should be able to:

• Describe a non-linear regression model

• Discuss the asymptotic properties of non-linear least squares estimators

• Describe the concepts of mixed models

• Estimate functions in non-parametric regression functions

• Explain the concepts of non-parametric regression functions

Course Notes

The Course Notes prepared are as follows:

• Course Outline

• Introduction to Statistical Model Building

• Model Building and Variable Selection

• Contigency Tables

• Generalized Linear Models

• Logistic Regression

• Poisson Regression

• Ridge Regression Notes