Available in 2018

Course handbook


This course presents various applied methods commonly used in the field of clinical biostatistics and medical research. Emphasis is placed on diagnostic assessment tools and screening tests.

Availability2018 Course Timetables

WebLearn GradSchool

  • Semester 1 - 2018

Learning outcomes

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

1. Understand the basic statistical methods used in applied clinical practice

2. Replicate the results of clinical case studies using SAS software;

3. Correctly employ these statistical methods and have the skills to effectively communicate with clinicians on the application of these 3. Critically assess the methodological strengths and weaknesses of published medical research.

4. Design a screening protocol;

5. Compare a new medical procedure/treatment against standard of care;

6. Compute power and sample size for applied medical research.


Case studies will be used to illustrate the medical application of various biostatistical methods and procedures including: Bayes’ rule and screening tests, ROC curves, sensitivity, specificity, accuracy, Mathew’s correlation coefficient, Bland-Altman plots, likelihood ratio of a positive/negative test, kappa statistic for clinical agreement, intraclass correlation coefficient, fixed and random effects models, meta-analysis, cluster binary data analysis, clinical prediction and outcomes research, and power/sample size estimation.

Assessment items

Written Assignment: Essays / Written Assignments

Contact hours

WebLearn GradSchool

Self-Directed Learning

Self-Directed 6 hour(s) per Week for Full Term

Suggest 8-12 hours of time commitment per week (guide only).