Data analysis is a central activity in applied epidemiology providing underlying evidence for public health policy formulation and action. Data may come from studies with survey, cohort or case control designs, or from health system surveillance or monitoring. The different types of data require different analytic methods appropriate to the form of the data and to the research question. This course aims to introduce students to some different types of quantitative public health data, with a focus on secondary dataset analysis, and to give students the opportunity for hands-on learning of epidemiological data analysis skills. The course is relevant to any student interested in a career in public health or health research, or to those wishing to extend their statistical skills to analysis of public health data.

Learning Outcomes

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

1. Define questions of public health significance appropriate to secondary dataset analysis
2. Design an analysis plan
3. Perform a descriptive analysis
4. Identify and use appropriate statistical analytic approaches and methods
5. Identify limitations of data analyses
6. Communicate findings for public health action

Recommended Resources

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
• access to Stata
• 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/systems/recommended-student-system-requirements

Staff Feedback

Students will be given feedback in the following forms:

• written comments
• feedback to whole class via the course WATTLE site

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.

Other Information

Prior to the start of the semester all students must complete an introductory online non-assessable quiz.

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Overview of the course Introduction to STATA and descriptive analysis	Lecturer: Sumonaknti Das / Elisabeth Huynh
2	Data management and data analysis plans	Lecturer: Sumonaknti Das
3	Multiple linear regression	Lecturer: Sumonaknti Das
4	Model selection for linear regression	Lecturer: Sumonaknti Das
5	Analysis of binary data	Lecturer: Katie Glass
6	Logistic regression	Lecturer: Katie GlassOnline Quiz will be available on Thursday of week 6 and close on Friday (covering weeks 1-5)Quiz time limit: 1.5-hour to complete once you have ‘logged in’
7	Conditional logistic regression	Lecturer: Katie GlassWritten Assignment 1 open Friday 19 Sep 2025 11:59 PM
8	Analysis of rates and count data	Lecturer: Nina Lazarevic
9	Poisson and negative binomial regression	Lecturer: Nina LazarevicWritten Assignment 1 due Friday 3 Oct 2025 11:59 PM
10	Survival analysis	Lecturer: Nina Lazarevic / Sumonkanti Das
11	Missing data	Lecturer: Erin WalshWritten Assignment 2 open Friday 17 Oct 2025 11:59 PM
12	Choosing tests and models	Lecturer: Alice Richardson
13	Exam period	Written Assignment 2 due Friday 31 Oct 2025 11:59 PM

Tutorial Registration

N/A

Assessment Summary

Assessment task	Value	Due Date	Return of assessment	Learning Outcomes
Online Quiz	40 %	29/08/2025	*	3,4
Written assignment 1: Statistical Analysis Plan	20 %	03/10/2025	17/10/2025	1,2
Written assignment 2: Statistical Analysis Report	40 %	31/10/2025	*	3,4,5,6

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

Policies

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:

• Academic Integrity Policy and Procedure
• Student Assessment (Coursework) Policy and Procedure
• Extenuating Circumstances Application
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure
• Code of practice for teaching and learning

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 ‘Canvas’ 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.

Participation

To succeed in this course, students are expected to develop strong skills in both data management and data analysis using Stata. This includes organizing, cleaning, and transforming data sets, as well as performing descriptive and inferential statistical analyses. Gaining fluency in Stata not only supports coursework but also prepares students for applied research and evidence-based decision-making in academic and professional settings. Active participation and hands-on practice will be key to mastering these essential tools—so please make the most of each 1.5-hour classroom session.

Assessment Task 1

Online Quiz

This will comprise a number of questions to assess your knowledge of the material covered. The online quiz will be available on the course Canvas site for a 48-hour period. You are required to log into the course Canvas site sometime during this period to complete the assessment. There will be a 1.5-hour time limit to complete the quiz once you have ‘logged in’. Once logged in, you must continue until you have completed the assessment as only one log in per student is allowed.

You are allowed to access any printed or internet based resources to complete the assessment, however you must not discuss the assessment with anyone else.

The online assessment will comprise multiple choice, true/false, short answer and some data analysis questions. For part of the assessment, you will need to download a dataset from the course Canvas site to answer some of the questions in that assessment.

Further details can be found on the course Canvas site.

Assessment Task 2

Written assignment 1: Statistical Analysis Plan

You will be given a scenario and a template and asked to write a Statistical Analysis Plan, based on the given information. The assignment should not exceed 1500 words (not including Tables, Figures and References).

Further details can be found on the course Canvas site.

Assessment Task 3

Written assignment 2: Statistical Analysis Report

You will be given a dataset from a study and asked to analyse the data and write a summary report of your analysis and interpret it. You will be required to submit an annotated “Do file” that summarises the code you used in Stata to conduct the analyses. The assignment should not exceed 2000 words (not including Tables, Figures, References and Appendices).

Further details can be found on the course Canvas site.

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

Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:

• Late submission permitted. Late submission of assessment tasks without an extension are 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 on the course WATTLE site for the return of the assessment item.

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. Any use of artificial intelligence must be properly referenced. Failure to properly cite use of Generative AI will be considered a breach of academic integrity.

Returning Assignments

Written assignments with comments will be returned via the course WATTLE site or student email.

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 is not permitted.

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).

• ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
• ANU Accessibility for students with a disability or ongoing or chronic illness
• ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
• ANU Academic Skills supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents all ANU students