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Unit of study_

BSTA5002: Principles of Statistical Inference

Semester 1, 2020 [Online] - Camperdown/Darlington, Sydney

The aim of this unit is 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. Content covered includes: review of the key concepts of estimation and construction of Normal-theory confidence intervals; frequentist theory of estimation including hypothesis tests; methods of inference based on likelihood theory, including use of Fisher and observed information and likelihood ratio; Wald and score tests; an introduction to the Bayesian approach to inference; an introduction to distribution-free statistical methods.

Unit details and rules

Unit code BSTA5002
Academic unit Public Health
Credit points 6
Assumed knowledge


Available to study abroad and exchange students


Teaching staff

Coordinator Liz Barnes,
Type Description Weight Due Length
Assignment Module 1 exercise
One exericse for submission
3.33% Multiple weeks
Due date: 15 Mar 2020 at 23:59
Mar 02 – Mar 15
Outcomes assessed: LO1 LO2 LO3
Assignment Module 2 exercise
One submissible exercise
3.33% Multiple weeks
Due date: 29 Mar 2020 at 23:59
Mar 16 – Mar 29
Outcomes assessed: LO1 LO2 LO3
Assignment Module 3 exercise
One submissible exercise
3.34% Multiple weeks
Due date: 12 Apr 2020 at 23:59
Mar 30 – Apr 12
Outcomes assessed: LO1 LO2 LO3
Assignment Assignment 1
Three questions covering material in modules 1-3
40% Multiple weeks
Due date: 26 Apr 2020 at 23:59
Apr 09 - Apr 26
Outcomes assessed: LO1 LO2 LO3
Assignment Module 4 exercise
One submissible exercise
3.33% Multiple weeks
Due date: 08 May 2020 at 23:59
Apr 27 – May 08
Outcomes assessed: LO1 LO2 LO3
Assignment Module 5 exercise
One submissible exercise
3.33% Multiple weeks
Due date: 20 May 2020 at 23:59
May 09 – May 20
Outcomes assessed: LO1 LO2 LO3
Assignment Module 6 exercise
One submissible exercise
3.34% Multiple weeks
Due date: 01 Jun 2020 at 23:59
May 21 – Jun 01
Outcomes assessed: LO1 LO2 LO3
Assignment Assignment 2
Three questions covering material in all modules
40% Multiple weeks
Due date: 14 Jun 2020 at 23:59
May 29 - Jun 14
Outcomes assessed: LO1 LO2 LO3

Assessment summary

6 submissible module exercises, of which your best 5 marks will each contribut 4% towards the total.

2 major assignments, each of which contributes 40% towards the total

Assessment criteria


Assessment name

Assessment type



Module 1 submissible exercise


Module 1


Module 2 submissible exercise


Module 2


Module 3 submissible exercise


Module 3


Assignment 1


Modules 1-3


Module 4 submissible exercise


Module 4


Module 5 submissible exercise


Module 5


Module 6 submissible exercise


Module 6


Assignment 2


Modules 1-6


* Your best five module marks will each contribute 4% towards the total of 20% for the module exercises


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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

The standard BCA policy for late penalties for submitted work is a 5% deduction from the earned mark for each day the assessment is late, up to a maximum of 10 days (including weekends and public holidays). Extensions are possible, but these need to be applied for (by email) as early as possible. The Unit Coordinator is not able to approve extensions beyond three days; for extensions beyond three days you need to apply to your home university, using their standard procedures.

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.

Required readings


Marchner, I.C.

Inference Principles for Biostatisticians

Chapman and Hall / CRC, 2014

ISBN 9781482222234


Sifting the evidence-what's wrong with significance tests? Sterne JA, Davey Smith G. BMJ 2001; 322: 226–31.

Does significance matter? R. Allan Reese Significance 2004; 1: 39–40.


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. Have a deeper understanding of fundamental concepts in statistical inference and their practical interpretation and importance in biostatistical contexts
  • LO2. Understand the theoretical basis for frequentist and Bayesian approaches to statistical inference
  • LO3. Be able to apply likelihood-based methods of inference, with particular reference to problems of relevance in biostatistical contexts

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.

The unit is regularly updated in response to student feedback. Since Semester 1 2019 the exercises have been altered to clarify cross-referencing between exercises and material referred to in previous modules.


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

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