Skip to main content
Unit of study_

PUBH5217: Biostatistics: Statistical Modelling

Semester 2, 2021 [Online] - Camperdown/Darlington, Sydney

In this unit, you will learn how to analyse health data using statistical models. In particular, how to fit and interpret the results of different statistical models which are commonly used in medicine and health research: linear models, logistic models, and survival models. This unit is ideal for those who wish to further develop their research skills and/or improve their literacy in reading and critiquing journal articles in medicine and health. The focus of the unit is very applied and not mathematical. Students gain hands on experience in fitting statistical models in real data. You will learn how to clean data, build an appropriate model, and interpret results. This unit serves as a prerequisite for PUBH5218 Advanced Statistical Modelling.

Unit details and rules

Unit code PUBH5217
Academic unit Public Health
Credit points 6
(PUBH5211 or PUBH5212 or PUBH5213)
Assumed knowledge


Available to study abroad and exchange students


Teaching staff

Coordinator Kevin McGeechan,
Type Description Weight Due Length
Assignment Assignment 2
Written assessment
55% Formal exam period To be added by unit coordinator
Tutorial quiz Quiz 1
Online quiz
5% Week 05 To be added by unit coordinator
Assignment Assignment 1
Written assessment
25% Week 07 To be added by unit coordinator
Tutorial quiz Quiz 2
Online quiz
5% Week 09 To be added by unit coordinator
Tutorial quiz Quiz 3
Online quiz
5% Week 11 To be added by unit coordinator
Tutorial quiz Quiz 4
Online quiz
5% Week 14 (STUVAC) To be added by unit coordinator

Assessment summary

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range


High distinction

85 - 100



75 - 84



65 - 74



50 - 64



0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. read a data file into statistical software
  • LO2. manipulate and edit data set in statistical software
  • LO3. conduct appropriate exploratory data analysis when the outcome variable is continuous, binary, or time-to-event using statistical software
  • LO4. fit a multiple linear regression model using statistical software, where the explanatory variables may be continuous and/or categorical
  • LO5. interpret the results from a multiple linear regression model
  • LO6. identify the difference between a potential confounder and actual confounder
  • LO7. conduct appropriate model building strategies for building a regression model
  • LO8. use statistical software to conduct appropriate model checking for linear regression models
  • LO9. use logistic regression to assess the association between a binary outcome and multiple covariates
  • LO10. use Poisson regression to assess the association between a count outcome and multiple covariates
  • LO11. write statistical software to analyse categorical data, and correctly interpret the produced output
  • LO12. identify when it is appropriate to use survival analysis methods, including the logrank method and Cox proportional hazards model
  • LO13. define censoring, the survivor function, and the hazard function
  • LO14. produce survival curves in a plot using statistical software and correctly interpret such a plot
  • LO15. perform logrank tests and fit Cox proportional hazards models to analyse survival data
  • LO16. assess the proportional hazards assumption, and describe what to do if this assumption does not hold
  • LO17. write statistical software to analyse survival data, and correctly interpret the produced output.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities

This section outlines changes made to this unit following staff and student reviews.

Students will have access to pre-recorded lectures as well as a live Q&A session.


The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.