Course Title: Sequential Analysis

Part A: Course Overview

Course Title: Sequential Analysis

Credit Points: 12.00


Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH1313

City Campus

Postgraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

Sem 1 2007

Course Coordinator: A/Prof Basil M de Silva

Course Coordinator Phone: +61 3 9925 2252

Course Coordinator Email: desilva@rmit.edu.au


Pre-requisite Courses and Assumed Knowledge and Capabilities

Basic concept of random variables and probability distributions; fundamentals of point estimation, interval estimation and hypotheses testing.


Course Description

Wald’s sequential probability ratio test; average sample number; sequential tests for composite hypotheses; sequential point and interval estimation; Stein’s two - stage procedure; asymptotic theory for sequential estimation; multi - stage sequential procedures; sequential bootstrapping. S - PLUS statistical computing package will be used.


Objectives/Learning Outcomes/Capability Development

You will improve or gain capabilities in:
• the application of sequential statistical techniques;
• critically examining sequential procedures for appropriate statistical analyses;
• the use of S-PLUS, statistical software package, to analyse data.


The course will cover both theory and applications of sequential procedures for point estimation, hypothesis testing and fix-width confidence interval estimation. The techniques unique to the sequential setting such as two-stage, three-stage and purely sequential procedures will also be covered in the course. Skills will be developed with S-PLUS, a leading statistical analysis software package.


Overview of Learning Activities

You will attend two hours of lectures per week. If you are experiencing difficulty in understanding the lecture material you may seek free help from the lecturer during the advertised consulting times.


Overview of Learning Resources

There will be a list of recommended textbooks for this course. In addition you will be given lecture notes and assignments


Overview of Assessment

Assessment of this course based on assignment work done during the semester and an end of semester examination.