• Class Number 2643
  • Term Code 3430
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery Online
    • Dr Tsheten Tsheten
    • Dr Tsheten Tsheten
  • Class Dates
  • Class Start Date 19/02/2024
  • Class End Date 24/05/2024
  • Census Date 05/04/2024
  • Last Date to Enrol 26/02/2024
SELT Survey Results

This course will examine principles of biostatistics, in the context of real-world public health issues. The aim of the course is to help those without a specialised background to read and interpret biostatistical content in the medical and public health literature.

Topics, chosen by frequency of occurrence in the literature, will include:

  • Introduction to sampling distributions, hypothesis tests and estimation
  • Analysis of normal data, including t-tests and linear regression
  • Analysis of binary data, including 2x2 tables, Mantel-Haenszel methods and logistic regression
  • Analysis of count data, including comparing rates between two groups
  • Poisson regression

Throughout the course, the emphasis will be on understanding the reasons why the techniques are appropriate, underlying assumptions, use of the statistical analysis package Stata and interpretation of results, rather than the mechanics of calculation. Each topic will draw upon one or two papers from the literature. Both online materials and drop-in help sessions in a computer lab will be used to facilitate learning and provide opportunities to explore specific topics in more detail.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Define and explain mathematical and biostatistical concepts covered in the course.
  2.  Produce appropriate visual displays and summary statistics for datasets, and describe the shape and properties of the data from those outputs.
  3. Choose and implement appropriate statistical models and tests and interpret their outputs to make inferences from data; continuous outcomes, binary data, categorical data, count data.
  4. Produce appropriate diagnostic plots for statistical models and use these to critically assess the assumptions of the model against the data.
  5. Construct functioning scripted statistical analysis (in STATA or R) to load, wrangle, and analyse a dataset.
  6. Critically assess the statistical methods and evidence presented in published research studies.

Research-Led Teaching

This course will use current research articles/projects to introduce students to interesting topics and problems in the field of biostatistics.

Additional Course Costs

This course will uses STATA for data analysis. Students will have access to a limited version of this program provided by ANU. Students who are interested in ongoing use of this program may wish to consider purchasing their own personal licence for STATA.

Required Resources

·       Betty R Kirkwood & Jonathan AC Sterne. Essential Medical Statistics (2e). Oxford: Blackwell Science Ltd, 2003.

‘Essential Medical Statistics’ is considered a classic among medical statisticians. An introductory textbook, it presents statistics with a clarity and logic that demystifies the subject, while providing a comprehensive coverage of advanced as well as basic methods. It is available for purchase from the Co-op Bookshop (Bldg #17 Union Court; Tel (02) 6249 6244). The Hancock Library (Bldg #43) also holds several copies for loan (RA407.K57 2003).


·       Stata B/E.

This course includes a hands-on introduction to the statistical analysis software Stata, the product of choice of most public health data analysts. You can use the software on computers in the Crawford Building (Bldg #132). It can also be purchased online through a company based in the ACT, https://www.surveydesign.com.au/stata/buy.html. You can buy a licence for as short as 6 months, or a perpetual licence.

If you find that there are sections that you are struggling with, try some supplementary reading of either of these books:

·        Bland, M. An Introduction to Medical Statistics (4e). Oxford: Oxford University Press, 2015.

·        Daniel W.W. & Cross, C.L. Biostatistics: A Foundation for Analysis in the Health Sciences (11e). New York: John Wiley & Sons, 2018.


If you are looking for an easy to read, non-mathematical introduction to medical statistics that concentrates on the concepts, and not the formulae, then try:

·        Motulsky H. Intuitive Biostatistics (4e). New York: Oxford University Press, 2017.

·        Campbell, M.J. Statistics at Square One (12e). London: BMJ Publishing Group, 2021.


If you want to delve deeper into the topic of biostatistics, try:

·        Armitage, P.; Berry, G. & Matthews, J.N.S. Statistical Methods in Medical Research (4e). Oxford: Wiley-Blackwell, 2002.

Recommended student system requirements 

ANU courses commonly use a number of online resources and activities including:

  • video material, similar to YouTube, for lectures and other instruction
  • two-way video conferencing for interactive learning
  • email and other messaging tools for communication
  • interactive web apps for formative and collaborative activities
  • print and photo/scan for handwritten work
  • home-based assessment.

To fully participate in ANU learning, students need:

  • A computer or laptop. Mobile devices may work well but in some situations a computer/laptop may be more appropriate.
  • Webcam
  • Speakers and a microphone (e.g. headset)
  • Reliable, stable internet connection. Broadband recommended. If using a mobile network or wi-fi then check performance is adequate.
  • Suitable location with minimal interruptions and adequate privacy for classes and assessments.
  • Printing, and photo/scanning equipment

For more information please see https://www.anu.edu.au/students/learning-platforms/recommended-student-system-requirements

Staff Feedback

Students will be given feedback in the following forms in this course:

  • through written comments on assignments
  • through verbal comments to indivduals / focus groups.

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Class Schedule

Week/Session Summary of Activities Assessment
1 Maths refresher
2 Variables and samples
3 Summarising and organising data
4 Sampling distributions and confidence intervals Assignment 1 released
5 Binary outcomes
6 Hypothesis testing I Assignment 1 due; Quizzes 1-3 due
7 Hypothesis testing II
8 Power and sample size Assignment 2 released
9 Correlation and simple regression
10 Multiple regression Assignment 2 due
11 Logistic regression
12 Poisson regression Take-home exam released; Quizzes 4-6 due

Tutorial Registration

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Online quizzes 1 - 3 6 % 28/03/2024 28/03/2024 1,2,3
Online quizzes 4 - 5 4 % 31/05/2024 31/05/2024 1,2,3
Assignment 1 20 % 28/03/2024 12/04/2024 1,2,3,6
Assignment 2 30 % 10/05/2024 24/05/2024 1,2,3,6
Take-home exam 40 % 06/06/2024 28/06/2024 1,2,3,4,5,6

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details


ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.


All content for the course is available online through the WATTLE site. Students are expected to be proactive in their learning from this material. Students should progress through the online material at a pace that keeps up with the progression of the course. Weekly tutorial/consultation participation is optional, but is strongly encouraged for students who require any assistance with the online material. The course lecturer will be available for assistance at the weekly tutorial/consultation sessions, and is also available for additional assistance as required. If you have any difficulties with any aspect of the material, please ensure that you engage with the course lecturer for assistance.

Assessment Task 1

Value: 6 %
Due Date: 28/03/2024
Return of Assessment: 28/03/2024
Learning Outcomes: 1,2,3

Online quizzes 1 - 3

These three quizzes are designed to provide quick feedback on your understanding of topics as the semester progresses. You may attempt the quiz once only. Each quiz is worth 2% of your final grade.

Assessment Task 2

Value: 4 %
Due Date: 31/05/2024
Return of Assessment: 31/05/2024
Learning Outcomes: 1,2,3

Online quizzes 4 - 5

These two quizzes are designed to provide quick feedback on your understanding of topics as the semester progresses. You may attempt the quiz once only. Each quiz is worth 2% of your final grade.

Assessment Task 3

Value: 20 %
Due Date: 28/03/2024
Return of Assessment: 12/04/2024
Learning Outcomes: 1,2,3,6

Assignment 1

This topic-based assignment is designed to reinforce understanding of the material covered in the relevant parts of the course. The questions are based on production and interpretation of computer output, and the biostatistical content of a published paper; both the question sheet and the published paper will be available on WATTLE.

Assessment Task 4

Value: 30 %
Due Date: 10/05/2024
Return of Assessment: 24/05/2024
Learning Outcomes: 1,2,3,6

Assignment 2

This topic-based assignment is designed to reinforce understanding of the material covered in the relevant parts of the course. The questions are based on production and interpretation of computer output, and the biostatistical content of a published paper; both the question sheet and the published paper will be available on WATTLE.

Assessment Task 5

Value: 40 %
Due Date: 06/06/2024
Return of Assessment: 28/06/2024
Learning Outcomes: 1,2,3,4,5,6

Take-home exam

The take-home exam is designed to reinforce understanding of the material covered over the whole course. The questions are based on production and interpretation of computer output, and the biostatistical content of a published paper; both the question sheet and the published paper will be available on WATTLE.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.


The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

For online quizzes, no submission of the quizzes after the due date will be permitted. If a quiz is not submitted by the due date, a mark of 0 will be awarded for that item.

For all other assessment items, late submission of assessment tasks without an extension will be permitted, but will be penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. For the take-home examiniation, all late submissions must occur within the ANU examination period.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Returning Assignments

Assignments will be returned via WATTLE.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

Resubmission of assignments will be at the discretion of the course convenor in consultation with the Associate Director (Education).

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Dr Tsheten Tsheten

Research Interests

Statistical Theory, Applied Statistical Analysis, Statistical Programming

Dr Tsheten Tsheten

By Appointment
Dr Tsheten Tsheten

Research Interests

Dr Tsheten Tsheten

By Appointment

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