PUB HLTH 7104 - Biostatistics

North Terrace Campus - Semester 2 - 2021

This course is designed to suit students requiring a high degree of self-sufficiency in the collection, analysis and interpretation of data. The topics will include non-parametric statistical methods, linear models, logistic regression, Generalized Linear Models and Poisson regression, and survival analysis. A central feature of the course will be instruction in the use of statistical packages on computers, primarily Stata. Emphasis will be placed on data management and manipulation, practical application of statistical skills to real data sets and interpretation of results

  • General Course Information
    Course Details
    Course Code PUB HLTH 7104
    Course Biostatistics
    Coordinating Unit Public Health
    Term Semester 2
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 3 hours per week
    Available for Study Abroad and Exchange N
    Prerequisites Credit standard in PUB HLTH 7074 or PUB HLTH 7074OL
    Restrictions Available to Grad Cert, Grad Dip, MPH & MHEP students only
    Course Description This course is designed to suit students requiring a high degree of self-sufficiency in the collection, analysis and interpretation of data. The topics will include non-parametric statistical methods, linear models, logistic regression, Generalized Linear Models and Poisson regression, and survival analysis. A central feature of the course will be instruction in the use of statistical packages on computers, primarily Stata. Emphasis will be placed on data management and manipulation, practical application of statistical skills to real data sets and interpretation of results
    Course Staff

    Course Coordinator: Associate Professor Lynne Giles

    Course Coordinator: Associate Professor Lynne Giles
    Phone: +61 8313 0234
    Location: Level 9, Adelaide Health and Medical Sciences Building
    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

    Timetable details are located on MyUni.
  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course, students will be able to:
    1 Manage and manipulate data efficiently and effectively;
    2 Apply a range of simple and complex statistical analysis techniques commonly used in Health Sciences appropriately;
    3 Demonstrate statistical reasoning skills correctly and contextually;
    4 Interpret results of statistical analyses in written summaries; and
    5 Use the statistical software package 'Stata' proficiently to conduct data manipulation and statistical analyses.
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    1, 2
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    2, 3, 4
    Teamwork and communication skills
    • developed from, with, and via the SGDE
    • honed through assessment and practice throughout the program of studies
    • encouraged and valued in all aspects of learning
    3, 4
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    1, 5
    Intercultural and ethical competency
    • adept at operating in other cultures
    • comfortable with different nationalities and social contexts
    • able to determine and contribute to desirable social outcomes
    • demonstrated by study abroad or with an understanding of indigenous knowledges
    Self-awareness and emotional intelligence
    • a capacity for self-reflection and a willingness to engage in self-appraisal
    • open to objective and constructive feedback from supervisors and peers
    • able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
    3, 4
  • Learning Resources
    Required Resources
    The textbook for this course is: Bland M.  Introduction to Medical Statistics.  4th edition.  2015; Oxford University Press, Oxford. 

    A copy of the textbook may be accessed via the High Use collection at the Barr Smith Library.

    Supplementary reading material and course notes will also be placed on MyUni.
    Recommended Resources
    The University of Adelaide recently introduced Project ADAPT: ADAPT is any Device, any Place and Time. Students can access Stata 13 (and other software including R, SPSS and MATLAB) from their home computers and their   portable devices (such as smartphones and tablets) via Project ADAPT. See the website above for more details.

    Students wishing to purchase their own copy of Stata will need to do so through Survey Design and Analysis Services (the Australian distributor of Stata; see There are several options in their Grad Plan packages; price is determined by the length of licence, with prices ranging from ~$100 to $200. Further details will be discussed in class.

    Useful texts and references will be discussed in class by the course co-ordinator. A very important resource for students encountering  any difficulties with mathematics or statistics at the University of Adelaide is the Maths Learning Centre based on Level 3 East of Hub  Central, North Terrace Campus. For details go to
    Online Learning
    General information about University computer laboratories is available at

    As an enrolled student, you will have access to the University’s on-line teaching facilities. This is an implementation of the  Blackboard system called MyUni. MyUni is accessible from the University of Adelaide’s home-page: . You will  need your student login name and a password.

    If you do not have access, then either you are not enrolled or the administrators of MyUni do not know of your enrolment. Please call Ask Adelaide on 8313 5208 (University extension 35208) or the IT help desk on 8313 3000 (University extension 33000) for assistance with MyUni difficulties.

    Selected documentation for this course will be placed on MyUni including lecture overheads, lecture recordings, computer practical  documentation, and data sets. Note also that Announcements about a course are often made on the relevant page of the MyUni  site for the course. For example, notifications of a change in lecture venue, updates on availability of course material etc. will be  made on the MyUni site.

    Students are assumed to have access to e-mail and that the address is the University of Adelaide student address that was  assigned on enrolment. This is of the form: A notice to a student by e-mail is considered  to have been received and read by the student unless there is a transmission error and the postmaster bounces the message back to us. As discussed above, the Announcements page of the MyUni site for this course will also display relevant notices   from time to time, so it is in students’ interests to check student e-mail and to log on to MyUni regularly.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    There are a number of teaching and learning modes in this course. The course lectures provide basic factual information and concepts in biostatistics. Due to the limited timeframe, not everything will be covered in lectures. Lectures are intended to supplement material covered in the readings. Lectures will be supported by interactive practicals which are designed to develop software skills and clarify topics covered in the readings and lectures. These are problem solving sessions and students are required to prepare for these sessions. Assignments provide an opportunity to undertake exploratory and in-depth analysis of some key concepts introduced in the course, and demonstrate their understanding of biostatistical concepts.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    As a general rule in any university course, you will need to allow a minimum of three independent study hours for every hour undertaken in formal class work contact. This means that, for Biostatistics, you will need to set aside at least further nine hours per week for reading around topics, preparation for practicals, and submitting your assignments. You are urged to bear this in mind when planning your university timetable, particularly if you are also engaged in paid employment. In our experience, students may not be able to demonstrate their full capacity if they are working full-time and studying full-time. Students are expected to attend all lectures and practicals as completion of readings alone will almost certainly not provide sufficient material to enable a pass.
    Learning Activities Summary
    Topic Lecture/Practical
    Managing data Lecture: Introduction, data sets, and statistical systems
    Practical: Getting started with Stata
    Non-parametric statistical methods Lecture: Exploratory data analysis, Sign test, Wilcoxon rank-sum test
    Practical: Manipulating data and working with dates in Stata
    Non-parametric statistical methods Lecture: Wilcoxon rank-sum test, Wilcoxon signed-rank test
    Practical: Assessing normality and non-parametric methods in Stata
    Linear Models 1 Lecture: Simple linear regression and regression diagnostics
    Practical: Linear regression and regression diagnostics
    Linear Models 2 Lecture: Multiple linear regression and model assumptions
    Practical: Fitting a multiple linear regression model
    Linear Models 3 Lecture: Analysis of covariance and model assumptions
    Practical: Anova and ancova in Stata
    Analysis of binary responses 1 Lecture: Measure of effect with binary data: Odds ratios, Mantel-Haenszel Odds ratios
    Practical: The Epitab suite
    Analysis of binary responses 2 Lecture: Simple and multiple logistic regression
    Practical: Logistic regression models
    Survival analysis 1 Lecture: Introduction to time to event data and life tables
    Practical: Life tables and survivorship functions
    Survival analysis 2 Lecture: Introduction to Cox proportional hazards regression models
    Practical: Fitting a Cox model in Stata
    Survival analysis 3 Lecture: Assessing the assumptions of Cox proportional hazards regression models
    Practical: Stratified Cox proportional hazards models
    Generalized Linear Models Lecture: Introduction to common Generalized Linear Models
    Practical: Poisson regression and glm
    Specific Course Requirements
    Small Group Discovery Experience
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Assessment Type Weighting Learning Outcome(s) being addressed
    Multiple choice quiz: Interpreting Stata output Summative 5% 2, 3, 4
    Data management and interpretation exercise Summative 35% 1-5
    Statistical analysis project Summative 50% 1-5
    Engagement in lectures and practicals Formative and summative 10% 3, 4
    Assessment Related Requirements
    To pass this course, you must achieve 50% overall, and a pass (50% or more) in the Statistical Analysis Project.
    Assessment Detail
    All assessment tasks will be distributed via hardcopy in lectures. All assessment tasks will be assessed according to the University's M10 mark scheme.
    All extensions for assignments must be requested, at the latest, by the last working day before the due date of submission.   Extensions will generally be granted only on medical or genuine compassionate grounds.  Supporting documentation must be  provided at the time a student requests an extension.  Without documentation, extensions will not be granted.  Late requests for  extension will neither be accepted nor acknowledged.

    Only the Course Co-ordinator(s) may grant extensions.
    Supporting documentation will be required when requesting an extension. Examples of documents that are acceptable include: a  medical certificate that specifies dates of incapacity, a police report (in the case of lost computers, car & household theft etc.), a  letter from a Student Counsellor, Education and Welfare Officer (EWO) or Disability Liaison Officer that provides an assessment of  compassionate circumstances, or a letter from an independent external counsellor or appropriate professional able to verify the  student’s situation.  The length of any extension granted will take into account the period and severity of any incapacity or impact  on the student.  Extensions of more than 10 days will not be granted except in exceptional circumstances.

    Late submission
    Marks will be deducted when assignments for which no extension has been granted are handed in late.

    All assignments, including those handed in late, will be assessed on their merits.  In the case of late assignments where no  extension has been granted, 5 percentage points of the total marks possible per day will be deducted.  If an assignment that is 2  days late is awarded 65% on its merits, the mark will then be reduced by 10% (5% per day for 2 days) to 55%.  If that same  assignment is 4 days late, the mark will be reduced by 20% (5% per day for 4 days) to 45%, and so on.

    The School of Public Health reserves the right to refuse to accept an assignment that is more than 7 days late.

    Assignments submitted after the due date may not be graded in time to be returned on the listed return dates.
    Students submitting examinable written work who request (and receive) an extension that takes them beyond the examination  period are advised that there is no guarantee that their grades will be processed in time to meet usual University deadlines.

    If a student is dissatisfied with an assessment grade they should follow the Student Grievance Resolution Process  <>.  Students who are not satisfied with a particular assessment result should raise their concerns with Course Co-ordinator(s) in the first instance.  This must be done within 10 business days of the  date of notification of the result.  Resubmission of any assignment is subject to the agreement of the Course Co-ordinator(s) and  will only be permitted for the most compelling of reasons.
    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy ( course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

The University of Adelaide is committed to regular reviews of the courses and programs it offers to students. The University of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.