Principles of Statistical Inference (PSI)

To provide a strong mathematical and conceptual foundation in the methods of statistical inference, with an emphasis on practical aspects of the interpretation and communication of statistically based conclusions in health research.


Semester 1: Ms Liz Barnes; NHMRC Clinical Trials Centre, University of Sydney

Semester 2: Dr Erin Cvejic and Ms Katrina Blazek; Sydney School of Public Health, University of Sydney

Ms Liz Barnes University of Sydney, NHMRC Clinical Trials Centre Semester 1
Dr Erin Cvejic University of Sydney, Sydney School of Public Health Semester 2
Ms Katrina Blazek University of Sydney, Sydney School of Public Health Semester 2
General outline


Mathematical Background for Biostatistics, Probability and Distribution Theory

Time commitment

8-12 hours total study time per week

Semester availability

Semester 1 & 2


Two major assignments worth 40% each and module exercises worth a total of 20%

Prescribed Texts

Marschner IC. Inference Principles for Biostatisticians. Chapman & Hall / CRC Pr, 2014. For details, including ISBN, see the BCA Textbook and Software Guide

Special Computer Requirements

R or Stata statistical software


Review of the key concepts of likelihood, and construction of Normal-theory confidence intervals; frequentist theory of estimation including hypothesis tests; methods of inference based on likelihood theory, including use of information and the likelihood ratio; Wald and score tests; an introduction to the Bayesian approach to inference; an introduction to distribution-free statistical methods.

Special Computer Requirements

Lectures, assignment material and interaction facilities available online