Simulation Methods in Medical Statistics

Description

With the availability of faster and more powerful computers, statistical simulations are being applied to an increasing range of problems in medical research where traditional methods do not provide a solution. This course aims to provide students with the theoretical and practical knowledge to apply simulation techniques to real-world problems.

Availability

WebLearn GradSchool

  • Semester 2 - 2017

Learning Outcomes

On successful completion of the course students will be able to:

1. Understand the rationale for statistical simulation and its potential applications;

2. Understand the concept of a Markov Chain and its potential applications;

3. Understand Monte Carlo methods and their applications to medical research;

4. Understand and utilize data resampling techniques such as bootstrapping and jackknife;

5. Use statistical software to perform a simulation study and then report the results in a manner suitable for publication;

Content

Students will learn to use simulation techniques to solve complex statistical problems in medical research. The concept of Monte Carlo methods will be further developed and combined with Markov Chains. Resampling methods will be explained and applied to a range of problems. Throughout the course the interpretation of results will be emphasised at a level suitable for publication.

Assessment Items

Written Assignment: Essays / Written Assignments

Contact Hours

WebLearn GradSchool

Online Activity

Online 6 hour(s) per Week for Full Term

Contact hours are an indication only.