Events listing - SSA events

To have your event added to this list, please forward the event details, including url, to

Upcoming events

    • 18 Nov 2019
    • 9:00 AM - 5:00 PM
    • Eliiza, Level 2, 452 Flinders St, Melbourne, VIC 3000

    * Registration is closed as of 2019/11/12 *

    Machine learning is a set of techniques that can reveal hidden patterns in data, and allows you to make predictive systems that grow ever more accurate the more data they learn from. Join us for two insightful workshops on machine learning and Python hosted by SSA Vic and Eliiza.

    Getting started with Machine Learning will cover the concepts and workflows involved in constructing these models. Getting started with TensorFlow will involve a deeper look into deep learning and the TensorFlow software framework, including the unique challenges involved in working with such models.

    Getting started with Machine Learning

    Morning workshop (9am to 12:30pm), presented by Patrick Robotham

    This is a hands-on course for making predictive models using machine learning. We will use Python libraries such as pandas and scikit-learn to analyse a dataset and make a predictive model.  We will then discuss ideas such as the bias-variance tradeoff for improving machine learning models and apply it to the models built earlier. Throughout the workshop you will program a sequence of Jupyter notebooks and gain experience in working with data in Python. The workshop will conclude with a discussion of how to deploy machine learning models into real world systems.

    At the end of this workshop you will be able to:

    • Use the Python libraries pandas and numpy to import and manipulate data
    • Use scikit-learn to construct linear and tree-based models
    • Know the difference between classification and regression
    • Evaluate a predictive model with appropriate metrics and plots
    • Improve a machine learning model using hyperparameter tuning.

    Getting started with TensorFlow

    Afternoon workshop (1:30pm to 5pm), presented by Patrick Robotham

    Neural networks are a family of machine learning models that can take data in a wide variety of formats and learn non-linear patterns in data by training millions of parameters simultaneously. Neural networks, also known as “Deep Learning”, have become more popular since they were used to win the 2012 ImageNet Challenge. This workshop will teach you how to use the TensorFlow framework to construct neural networks and apply them to tasks such as image recognition.

    The workshop will cover:

    • The backpropagation algorithm
    • The keras functional API
    • Convolutional Neural Networks
    • Recurrent Neural Networks
    • Data representation of images and sound
    • Deploying networks into production.

    At the end of the workshop you will be able to:

    • Train a neural network to recognise images
    • Implement neural network papers
    • Develop your own neural network architectures for your problem
    • Apply machine learning workflows to deep learning.

    About the presenter

    Patrick Robotham is a Data Scientist working for Eliiza. He regularly develops machine learning models for clients to solve business problems. He has 5 years of professional data science experience and works with RMIT Online as a mentor teaching Introductory AI courses.


    • Basic knowledge of Python will be assumed. We expect you to know how to write basic Python functions.
    • You will need to bring your own laptop (with administrative rights) to the workshops.


    Eliiza, Level 2, 452 Flinders Street, Melbourne


    Full day (both workshops)
    Half-day (1 workshop)
    Student member  $99 $65
     Member $199 $135 


    $299  $200 

    Member prices are available to SSA members or employees and special guests of the Mantel Group.  Lunch will be provided for all participants.

    Cancellation policy

    Cancellations received prior to 11 Nov 2019 will be refunded, minus a $20 administration fee. From 11 Nov 2019 onwards, no part of the registration fee will be refunded.

    • 18 Nov 2019
    • 12:00 PM - 1:00 PM
    • via Zoom, AEDT

    Please join us for a webinar with presenter A/Professor Agus Salim, 
    Mathematics and Statistics, La Trobe University and Baker Heart and Diabetes Institute.

    About the webinar:
    In the last few years, technological advance has enabled RNA sequencing to be carried out at single-cell level.  Single cell RNA-seq (scRNA-seq) data offers opportunities to discover novel cell-types and better understanding of cell heterogeneity and differentiation pathways. On the other hand, there are inherent challenges in scRNA-seq data analyses, many of which are shared with the bulk data, while some are unique to single-cell data. Owing to the small amount of biological material within a cell and imperfect technology, total and partial molecule dropout is a common phenomenon with scRNA-seq data, resulting in sparse dataset with often more than 90% zero counts. In this talk, I am going to discuss DECENT (Differential Expression with Capture Efficiency adjustment), our approach for modelling molecule dropout using beta-binomial model and demonstrate using four real datasets, how correct modelling of dropout lead to better identification of cell type-specific marker genes.

    About the presenter
    Dr Agus Salim is Associate Professor at the Department of Mathematics and Statistics, La Trobe University. He came to La Trobe in April 2013 having previously held positions at the Australian National University and National University of Singapore. Agus has over 15 years experience as a biostatistician and has extensive records of collaboration with clinicians and epidemiologists and has received competitive funding from the National Health and Medical Research Council for his applied and methodological works. His main methodological interest is in the area of survival analysis with a focus on analysis of nested case-control data and the analysis of high-throughput data from next-generation sequencing.

    To register
    This is a free event, but you will need to register. Click here to save your place. After registering, you will receive a confirmation email containing information about joining the meeting.

    Would you please note that this event will be held at 12:00 PM AEDT? Please check your time zone!

    • 19 Nov 2019
    • Gold Coast

    Researcher Education and Development are pleased to invite you to attend a 2-part workshop 

    Bayesian Logistic Regression in Practice, using R or Autostat

    Who should attend? Anyone interested in analysing how several explanatory variables (aka predictors, independent variables, or inputs) and how they are related to a dichotomous response variable (aka outcome, dependent variable, or output). E.g., what affects your survival in a shipping disaster? What matters: whether you are male or female, or your age and passenger class? Or what kinds of habitat & climate are associated with species presence?

    What knowledge is assumed? Ideally you have conducted some form of regression before, and are familiar with the basic ideas of statistical modelling. This may have been in any statistical paradigm. With classical training you would understand: p-values to assess significance of effects, reporting of confidence intervals, and model diagnostics such as R-squared, AIC and residuals. With training in machine learning you may be familiar with cross-validation and variable selection through stepwise selection or lasso. You need no knowledge of Bayesian statistical modelling.

    What preparation is needed? 
    Participants will use either AutoStat or R.   To streamline the provision of data and notes, those using R will be invited to do so through the AutoStat GUI.   Please bring your laptops.  An email will be sent prior to the workshop with account details and login instructions.  You will not be required to load any software on your personal computer.

    What will be learned?

    Part 1: Meaning and Eliciting Knowledge. We start by considering the role of variables in statistical modelling, and in particular, how these form the basic building blocks of a linear regression model. Importantly, we address the logic behind regression, and how this affects model-building and interpretation, when establishing: association (e.g. co-relation) between various factors; or causality, where some factors influence another. The first case study on shipping disasters examines how survival of people on board relate to factors such as demographics (age, gender) and class. A second case study on koalas examines how reported sightings relate to habitat and climate factors.

    In this way, by examining linear regression through a model-based lens, we set the groundwork for introducing the concept of a logistic regression. The major difference between the two statistical models is the kind of outcomes that they are suitable for: dichotomous (like survival/death or presence/absence) vs continuous outcomes (like age and ticket cost or habitat/climate). We show how this major difference has subtle impact on implementation.

    We show how explanatory factors—which may be continuous, dichotomous or categorical—contribute to explain the expected outcome. In this way, we build up your understanding of both linear and logistic regression by gradually introducing equations, at first using diagrams, then words, and real numbers. Only briefly do we refer to the Greek notation of classical statistics. We include a pictorial introduction to the logit transformation (aka “log odds ratio”) at the heart of logistic regression.

    We then show how to use this understanding to elicit relevant information from experts or the literature. We show you several ways of talking with experts to elicit such information. For illustration: we analyse one shipping disaster, and then use this information to inform analysis of the “next” disaster; and analyse koala presence in one region, and then use this information to help map presence in another.

    Part 2. Inference and computation for Bayesian logistic regression, including informative priors.

    This second workshop, in a two-part series, focuses on more intermediate level concepts. We assume that you attended Part 1 (or have equivalent prior learning), which focused on how to understand and communicate the meaning of the model for logistic regression, and also elicited priors for the parameters. In Part 2, we progress beyond understanding the results of logistic regression to how to obtain these results.

    We contrast classical Maximum Likelihood and Bayesian approaches to inference for logistic regression. Importantly this means exposing the limitations of a Frequentist approach, which can to some degree be addressed via Bayesian computation and/or inference. In particular, we consider interpretation of p-values, properties of the Wald statistic and other model fit criteria in the classical logistic regression framework. We explore the practical assessment of interactions, and strategies to counter common pitfalls, such as separation and perfect prediction. These are contrasted with Bayesian interpretation of credible intervals, highest posterior intervals, Bayes Factors and the use of posterior predictive checks to evaluate fit, and of convergence diagnostics to check computation. We demonstrate that the Bayesian approach circumvents issues of separation.

    What is the main objective?

    In this two-part series (Parts 1 and 2), we aim to develop your ability to critically understand and evaluate the results of a linear or logistic regression, produced in either a classical or Bayesian setting, and hence interpret output from standard statistical software and in published studies. Although you will gain hands-on experience doing logistic regression in your preferred software package (with support here for either R or Autostat), the emphasis will be on interpreting the outputs, which can be obtained using many different packages.

    In this way, we guide you to develop basic statistical literacy skills in explanatory or predictive modelling using linear or logistic regression. In addition, we share techniques for eliciting and encoding prior information into statistical distributions. These not only consolidate and test your understanding of the regression models, they also prepare a foundation for many useful skills in: capturing the current state of knowledge before data is collected using an expert model (a prior predictive); preparing for the next study via modern techniques for design (e.g. simulations for sample size analysis); updating the current state of knowledge about effects (via priors in a Bayesian regression); or consolidating multiple sources of information via a classical meta-analysis (of effect sizes).

    What form of teaching can I expect?

    We emphasize an active learning approach, and encourage you to “try things out” as you go. Thus both workshops will oscillate between short presentations of concepts and activities, to give you time to practice, probe and discuss those skills. You may wish to work in pairs or threes, to overcome minor stumbling blocks in a timely fashion and also deepen your learning through critical debate and reflection. However, we support a preference to work alone.

    We motivate and illustrate new concepts using a case study about shipping disasters.

    Beginners will be encouraged to use the easy workflow and menus of the Autostat environment. Those with experience (or interest) in R may choose whether to use Autostat, and write R scripts that can be executed from within Autostat, or to work within R studio directly.



    Assoc Prof Sama Low-Choy enjoys working with motivated investigators to answer questions that require statistical analysis. She is the Senior Statistician in the Office of the Pro-Vice Chancellor, Arts, Education & Law, Mt Gravatt campus, Griffith University. She takes a flexible and pragmatic approach, matching the problem, skills and resources to an appropriate paradigm: frequentist or Bayesian, parametric or non-parametric, or machine learning.


    Dr Clair Alston-Knox is a a Senior Statistician with Pacific Analytics Group, Melbourne and is an Adjunct in the Office of the Pro-Vice Chancellor, Arts, Education & Law, Mt Gravatt campus, Griffith University.Her recent transition from an academia to a commercial environment has enabled her to become part of a large team of specialist analysts who are working on the development of AutoStat®, a new cloud based software providing access to a suite of statistical, ML and AI algorithms.


    Daniela Vasco is a Ph.D. candidate at Griffith University. Her thesis in Applied Statistics is aligned with ARC Discovery Project on “Learning for Teaching in Disadvantaged Schools" led by Prof Parlo Singh and co-Principal supervisor is Assoc Prof Low-Choy. Her interests are statistical modelling of complex problems, model diagnostics, visualisation, and Bayesian inference and decision theory.


    November 19, 2019 
    Part 1: Understanding and elicitation
    November 28, 2019

    Part 2: Inference and implementation 

    Gold Coast campus
    10:00 AM - 4:00 PM 

    HDR candidates (external to Griffith University) : $150.00 per day

    Members of either SSA or ASBA : $200.00 per day

    Registrants external to Griffith University other listed than above : $250.00 per day

    Please indicate your attendance by November 15, 2019

    Click here to register. 

    Follow RED on Social Media for up to date event information
    facebook_red @researchereducdev         twitter_red @researcheducdev

    • 19 Nov 2019
    • 9:00 AM - 5:00 PM
    • Room 253, Arts West - North Wing, University of Melbourne

    * Registration is closed as of 12/11/2019 *

    R is an interactive environment for data analysis and statistical modelling. Join us for two insightful workshops on R skills hosted by SSA Vic and Melbourne Integrative Genomics (MIG).

    When performing data analyses, you typically need to share your insights with others. In our morning workshop, you will learn how to put your R code together into a 'package', which makes it easier to use and very easy to share. Then in our afternoon workshop, you will learn how to share and communicate the results of your analyses with others (and your future self!) using R Markdown.

    Building R packages

    Morning workshop (9am to 12:30pm), presented by Damjan Vukcevic

    You have developed a new statistical method. Now it is time to share it with the world.

    The methods that actually get used in practice are those with readily available and user-friendly implementations. Writing and disseminating software is therefore a key skill for modern statisticians, one that is generally not taught widely. This course aims to fill the gap.

    The R software environment is widely used for statistical analyses. One of its distinguishing features is the extensive range of R ‘packages’, which anyone can write and share via the internet. This used to be an intimidating process but modern tools have made it simple.

    We begin our course with how to write a very basic package, and then show how to include documentation, examples and data. Further topics include: an efficient development workflow, managing relationships between packages, sharing your packages with others, and easy ways to manage packages (finding, installing, upgrading).

    R Markdown

    Afternoon workshop (1:30pm to 5pm), presented by Emi Tanaka

    No matter how great your analysis, there is great benefit from streamlining your analysis to produce reproducible reports that can be easily disseminated. R Markdown can easily intermingle code and text to generate captivating, dynamic reports and presentations.

    The workshop will include in-depth explanation of the three main components of R Markdown: YAML, code chunks and text. These will be followed by hands-on exercises for you to dive straight into practising. You will learn how to: customise your documents with different output formats (e.g. Word, PDF or HTML); modify tables and figures; generate parametrised reports; make your document writing efficient and make beautiful slides with interactive components well-suited for data-storytelling or showcasing how your R package works.

    About the presenters

    Damjan Vukcevic is a Senior Lecturer in Statistical Genomics at the University of Melbourne, and the President of SSA Vic. R is his tool of choice for his work. He teaches introductory R to hundreds of statistics students every year, and has delivered the Building R packages workshop multiple times around Australia.

    Emi Tanaka is a Lecturer in Statistics at the University of Sydney, soon to join Monash University, and the Secretary of SSA NSW. She is an experienced and enthusiastic R user and instructor. She teaches R regularly to university students and has taught several R workshops including on Tidyverse, Blogdown, Shiny and R Markdown.


    • Basic knowledge of R will be assumed. We expect you to have used R to load data, create simple visualisations, perform basic analyses and write simple functions.
    • (R Markdown workshop only) Basic knowledge of LaTeX is desirable, but not essential.
    • You will need to bring your own laptop (with administrative rights) to the workshops.


    Room 253, Arts West - North Wing, University of Melbourne


    Full day (both workshops)
    Half-day (1 workshop)
    Student member  $99 $65
     Member $199 $135 


    $299  $200 

    Member prices are available to SSA members or staff and students of the University of Melbourne or an affiliate institution.  Lunch will be provided for all participants.

    Cancellation policy

    Cancellations received prior to 11 Nov 2019 will be refunded, minus a $20 administration fee. From 11 Nov 2019 onwards, no part of the registration fee will be refunded.

    • 19 Nov 2019
    • 9:00 AM
    • 20 Nov 2019
    • 5:00 PM
    • UQ's Institute for Social Science Research, Cycad Building, 80 Meiers Road, Indooroopilly

    Generate new knowledge through qualitative discovery.

    This course will enable participants to understand the results from administrative or survey data by investigating these findings in more depth through qualitative methods. It will cover skills to gather data from stakeholders through interviews, focus groups or visual methods in order to make evidence-informed decisions and ensure that surveys provide valid and reliable data.​

    For more information please click here.

    • 21 Nov 2019
    • 25 Nov 2019
    • Melbourne
    With major support from the Melbourne Academic Centre for Health (MACH) and co-sponsorship from Monash Partners and ACTA, ViCBiostat are conducting 3 days of workshops to assist policy makers, clinician researchers, early career researchers and biostatisticians understand the options and merits of various pragmatic randomised designs to evaluate the impact of health policy and practice change interventions. For more information please follow this link:

    • 25 Nov 2019
    • 8:30 AM
    • 27 Nov 2019
    • 5:00 PM
    • Surfers Paradise, Gold Coast

    Bayesian Research and Applications Group (BRAG) warmly invite you to a meeting of people involved or interested in Bayesian Research and Applications.

    Bayes on the Beach 2019 is the 13th International Workshop for the Australasian chapter of the International Society for Bayesian Analysis (ISBA) and the biennial meeting of the Bayesian Statistics section of the Statistical Society of Australia (SSA).

    Bayes on the Beach will be held at the Mantra Legends Hotel at Surfers Paradise, Gold Coast during November 25th -27th 2019. The conference provides a forum for discussion on developments and applications of Bayesian statistics, and includes keynote presentations, tutorials, practical problem-based workshops, invited oral presentations, and poster presentations.

    For details and regular updates please visit the full conference website.

    • 26 Nov 2019
    • 9:00 AM
    • 28 Nov 2019
    • 5:00 PM
    • UQ's Institute for Social Science Research, Cycad Building, 80 Meiers Road, Indooroopilly

    Develop skills to understand & conduct CBAs for social projects. This course is designed for professionals who need to engage with CBAs to aid the design & evaluation of public programs & policies, & need hands-on skills to conduct CBAs. This course equips participants with an understanding & working knowledge of the skills required to apply Cost-Benefit Analysis (CBA) to the appraisal & evaluation of projects with mainly social costs & benefits. The course will cover the potential uses & limitations of cost-benefit analysis (CBA), introduce Social Return on Investment (SROI) analysis, examine the principles & methods underlying CBA & non-market valuation, & provide hands-on exercises to practice the basic skills required to perform CBAs.

    When: 26 – 28 November 2019, 9am – 5pm

    Location: UQ's Institute for Social Science Research, Cycad Building, 80 Meiers Road, Indooroopilly

    For more information please click here

    • 26 Nov 2019
    • 6:30 PM - 8:30 PM (UTC+08:00)
    • Perth

    Dear members,

    The SSA WA branch end of year dinner is fast approaching. See the attached flyer or below for further information.

    The SSA WA Branch warmly invites you to our end of year dinner at Itsara.

    Date: Tuesday the 26th of November
    Time: 6.30pm
    Venue: Itsara, 25 Stirling Hwy, Nedlands WA. 
    Price: $35 for members and up to one guest, $25 for student members and $57 for other guests
    What’s Included: A banquet style dinner. Dessert may be purchased at extra cost.
    RSVP: By Friday the 15th of November with any special dietary requirements to

    Kind regards,
    WA Branch Treasurer

    • 28 Nov 2019
    • 29 Nov 2019

    We will be holding the third Workshop Organized by the Monash Business Analytics Team (WOMBAT) on 28-29 November 2019, focusing on statistical methods and tools for effective data analysis.

    Keynote speakers are Hadley Wickham and Galit Shmueli, with a stellar line up of invited speakers as well.

    Further details and registration is via the website at

    • 29 Nov 2019
    • QUT, Brisbane

    There is increasing international interest and engagement in the concept of ‘data science for social good’, with volunteers and organisations working on issues such as human rights, migration, social justice and so on. Having even more access to big data sources such as mobile phone data, satellite images and social media data brings many opportunities for new insights into these important problems, but there is a corresponding responsibility for appropriate analysis and interpretation of these data. The purpose of this symposium is to promote the merger of data science and social good, share success stories, discuss challenges and potential solutions, extend networks, and explore directions for new research.

    For more information – please go to: Data Science and Social Good Symposium: Friday 29 November 2019. To register, please click here.

    • 1 Dec 2019
    • 2 Dec 2019
    • University of Adelaide

    We have an exciting line-up of 7 workshops at The University of Adelaide in December!

    Workshop on 1st December  

    • Analyzing dependent data with vine copulas

    • Tidyverse & R Markdown Workshop

    • Whole Genome Analysis with wgaim

     Workshop on 2nd December

    • Identifying, randomizing, canonically analyzing and formulating mixed models for designs for comparative experiments using R

    • Handling missing data in administrative studies: multiple imputation and inverse probability weighting

    • Shiny App Development

    • An Introduction to Deep Learning with Biometric and Environmetric Applications

    Find more information here and registration here (you do not need to register for the conference to register for the workshops).

    • 2 Dec 2019
    • 5 Dec 2019
    • Adelaide

    The Australasian Data Mining Conference has established itself as the premier Australasian meeting for both practitioners and researchers in data mining. It is devoted to the art and science of intelligent analysis of (usually big) data sets for meaningful (and previously unknown) insights. This conference will enable the sharing and learning of research and progress in the local context and new breakthroughs in data mining algorithms and their applications across all industries. For more information please click here.

    • 3 Dec 2019
    • 6 Dec 2019
    • National Wine Center, Adelaide

    Come join the International Biometrics Society Australasian Region's biannual conference in Adelaide!

    • 3 Dec 2019
    • 5:00 PM (UTC+10:00)
    • 55 Railway Terrace, Milton

    • 3 Dec 2019
    • 7:00 PM - 8:00 PM
    • via Zoom, check local time

    The Statistical Society is pleased to announce the following webinar:

    Communicating risk and uncertainty with Sir David Spiegelhalter

    on 3 December 2019 from 7:00pm - 8:00pm AEDT via Zoom.

    About this webinar
    The claim of a 'post-truth' society, in which emotional responses trump balanced consideration of evidence, presents a strong challenge to those who value quantitative and scientific evidence: how can we communicate risks and unavoidable scientific uncertainty in a transparent and trustworthy way?

    Communication of quantifiable risks has been well-studied, leading to recommendations for using an expected frequency format. But uncertainty about facts, numbers, or scientific hypotheses needs to be communicated without losing trust and credibility. This is an empirically researchable issue, and I shall describe some current randomised experiments concerning the impact on audiences of alternative verbal, numerical and graphical means of communicating uncertainty.

    About the presenter
    Professor Sir David Spiegelhalter is Chair of the Winton Centre for Risk and Evidence Communication in the University of Cambridge, which aims to improve the way that statistical evidence is used by health professionals, patients, lawyers and judges, media and policy-makers. He advises organisations and government agencies on risk communication and is a regular media commentator on statistical issues, with a particular focus on communicating uncertainty.
    His background is in medical statistics, and he has over 200 refereed publications and is co-author of 6 textbooks, as well as The Norm Chronicles (with Michael Blastland), and Sex by Numbers. He works extensively with the media, and presented the BBC4 documentaries "Tails you Win: the Science of Chance", the award-winning "Climate Change by Numbers", and in 2011 came 7th in an episode of BBC1's "Winter Wipeout".

    He was elected Fellow of the Royal Society in 2005, and knighted in 2014 for services to medical statistics. He was President of the Royal Statistical Society for 2017-2018. His bestselling book, The Art of Statistics, was published in March 2019.

    He is @d_spiegel on Twitter, and his home page is

    To register
    This is a free event, but you will need to register. Click here to save your place. After registering, you will receive a confirmation email containing information about joining the meeting. 

    Would you please note that this event will be held at 7:00 PM AEDT? Please check your time zone! 

    • 6 Dec 2019


    6pm Friday 6th December

    This year's Cornish Lecture will be given by Marti Anderson (Massey University) so make sure you add this to your diary. More details to follow.

    • 6 Dec 2019
    • 5:00 PM - 6:00 PM
    • G04 Napier Lecture Theater

    B&B Networking event

    • Co-hosted by the SSA Biostatistics and Bioinformatics Section and the SSA SA Branch, the B&B networking event will be held at the G04 Napier lecture theater, University of Adelaide prior to the Cornish Lecture on 6th of December.
    • This informal event aims to bring together biostatisticians, bioinformaticians and other like-minded individuals to provide an opportunity for socializing and making connections.
    • All SSA and non-SSA members are welcome and encouraged to join this event.
    • Attendees are also welcome to join the Cornish lecture where Marti Anderson will be presenting.
    • Light refreshments and drinks will be provided.
    • This is a free event so please don't hesitate to register for this event.
    • 6 Dec 2019
    • 6:15 PM - 7:30 PM (UTC+10:30)
    • Napier G04 Lecture Theatre, North Terrace, The University of Adelaide

    E. A. Cornish Memorial Lecture

    South Australian Branch of the Statistical Society of Australia

    The South Australian Branch of the Statistical Society warmly invite you to attend the 2019 E. A. Cornish Memorial Lecture, to be given by Professor Marti J. Anderson. Held every two years, this lecture is the highlight of our speaker program and we look forward to seeing you there.

    Venue: Napier Building, G04 Lecture Theatre, North Terrace, The University of Adelaide. A campus map is available at


    5pm - 6pm - Biostatistics and Bioinformatics networking event

    Member and non-members can attend.

    Registration required. Please register, free of cost.

    Hosted jointly with the SSA Biostatistics and Bioinformatics Section and the SSA SA Branch.

    6:15pm - E. A. Cornish Memorial Lecture

    8pm - A dinner will be held after the meeting at The Griffins Hotel, 38 Hindmarsh Square, Adelaide SA 5000. Please RSVP for dinner to Paul Sutcliffe ( by Friday 29th November.

    Speaker: Distinguished Professor Marti J. Anderson, New Zealand Institute for Advanced Study (NZIAS), Massey University, Albany, Auckland, New Zealand

    Topic: Nonlinear models of species-environment relationships, with modern tools for misbehaving errors


    Species are being destroyed faster than they are being discovered. Despite growing repositories of global ecological data, current models of species' responses to broad-scale spatio-environmental gradients (such as temperature, latitude, depth, nutrients, moisture, or elevation), are either overly simplistic (Gaussian), or they are a "black box" without meaningful interpretable parameters. Furthermore, real ecological data are messy. Raw counts of individuals or biomass from broad-scale field surveys have no upper bound, and typically display large residual variance, over-dispersion and zero-inflation. In this lecture, I will outline a novel class of flexible models that combine new nonlinear mathematical functions for mean species' response curves with an array of modern multi-species distributions tailored to accommodate abundance, biomass or functional traits. Enhancing this even further, we can use flexible copulas to model multi-species associations in either their mean response along a given gradient, or in their (quite disparate types of) error distributions. From coniferous forests on mountain-tops to fishes in the deep blue sea, I will show a variety of key examples to demonstrate how this unique statistical framework can successfully capture and quantify global-scale responses of ecological communities to environmental change. The aim is to provide radical clarity on species' joint responses (through time and space), for important decisions that can change our world.


    Distinguished Professor Marti J. Anderson (Massey University, New Zealand) is an ecological statistician whose work spans several disciplines, from ecology to mathematical statistics. A Fellow of the Royal Society of New Zealand, and a recent recipient of a prestigious James Cook Fellowship, she holds the Professorial Chair in Statistics in the New Zealand Institute for Advanced Study (NZIAS) at Massey University in Auckland. Her core research is in community ecology, biodiversity, multivariate analysis, models of ecological count data, experimental design and resampling methods, with a special focus on creating new applied statistics for ecology that can yield new insights into global patterns of biodiversity. Marti is also the Director of PRIMER-e (Quest Researcher Limited), a boutique research and software development company that creates user-friendly software (PRIMER and PERMANOVA+) to implement robust multivariate statistical methods for ecological analysis and synthesis.

    The E. A. Cornish Lecture Series

    The Statistical Society of Australia, South Australian Branch, inaugurated a series of public lectures on statistical topics of broad interest in 2001. The lecture series has been named to commemorate Alf Cornish, a leading figure in the early years of the statistical profession in Adelaide.

    The lectures are held biennially and presented by eminent statisticians from around the world. Previous presenters of the Cornish Lecture have been Professor Terry Speed on the topic "Gene expression", Professor Adrian Baddeley on "Practical analysis of spatial points patterns", Professor Kerrie Mengersen on "Making decisions based on data", Denis Trewin "Statistical critique of the International Panel on Climate Change's work on climate change", Dr Louise Ryan "Data, data, everywhere!", Professor Peter Diggle on "A tale of two parasites: model-based geostatistics and river blindness in equatorial Africa", Professor Noel Cressie "Statistical science: A tale of two unknowns", Professor John Carlin "Statistics and statisticians in real-world research: science or snake-oil" and Professor Robert Elliott, "New ideas in an old framework".

    Edmund Alfred Cornish (1909-1973)

    E. A. Cornish graduated from Melbourne University in 1931 with first class honours in Agricultural Biochemistry, Agricultural Engineering and Surveying. While working as an astrostologist (specialist in grasses) at the Waite Research Institute, a centre for agricultural research and development in Adelaide, he became interested in statistical issues arising in agriculture. His interest in patterns of rainfall and their relationship to the yield of natural pastures continued throughout his life.

    In 1937 he took a leave of absence at his own expense to study statistics with R. A. Fisher in London. On his return, he was appointed statistician to the Waite Institute. In 1940 he was appointed as Officer-in-Charge of the Biometric Section of the Council for Scientific and Industrial Research (CSIR, now CSIRO) in Melbourne. Under his leadership, the Biometric Section grew, attracting such high caliber scientists as Evan Williams, George McIntyre and Helen Newton Turner. In 1944 the headquarters of the Section was moved to Adelaide and renamed the Mathematical Statistics Section; in 1954 it became the Division of Mathematical Statistics (DMS), with Cornish as its first Chief. Under his leadership DMS grew to 50 staff at his death in 1973.

    During the late 1950s, the University of Adelaide had become aware of the importance of mathematical statistics and appointed Cornish as Foundation Professor of Mathematical Statistics at the University of Adelaide from 1960 until 1965, when his former student Alan James returned from Yale to take over the role.

    While his name is perhaps most often heard in connection with the Cornish-Fisher expansion of quantiles of the distribution of a mean in terms of cumulants, his contributions to statistics and the profession were broad and of considerable significance for the development of statistics in Australia.

    In addition to his early work on rainfall, he published extensively on experimental designs and analysis of experimental data, particularly in the presence of missing values. His work with Fisher led him to a strong interest in fiducial theory. This led him to develop ground-breaking ideas in multivariate analysis, including the development of a multivariate t-distribution to obtain fiducial distributions of multivariate means.

    He was enthusiastic about the use of electronic computers in statistical work, perhaps as a result of his work on climatology, which involved the calculation and modelling of 90585 correlation coefficients. He appreciated early the potential for simulation to answer intractable statistical problems, and promoted the establishment of CSIRO's Division of Computing Research, whose successor, the Division of Information Technology joined with Division of Mathematics and Statistics (DMS) to form the Division of Mathematical and Information Sciences, which currently is known as Data 61 (the largest data innovation group in Australia).

    He was a Fellow of the Australian Institute of Agricultural Science, an Honorary Fellow of the Royal Statistical Society and  Fellow of the Australian Academy of Science. He also served as President of the International Biometric Society and of the Australasian Region.

    Alf Cornish laid the foundations for the strong tradition of experimental and theoretical statistics in Adelaide and it is fitting that his name should be associated with a series that will bring eminent statisticians to Adelaide to support the ongoing strength of the statistical profession here.

    Feel free to forward this meeting notice to colleagues, all welcome.

    • 9 Dec 2019
    • 9:00 AM
    • 13 Dec 2019
    • 5:00 PM
    • UQ's Institute for Social Science Research, Cycad Building, 80 Meiers Road, Indooroopilly

    Deepen your specialist knowledge of longitudinal approaches. This five-day intensive course has been specifically designed to deepen the specialist knowledge of your research teams and enhance the quality and meaning of the data you use when making crucial business decisions.

    The course delves deeply into topics that are pivotal for organisations that use longitudinal data for research and decision-making. Using an engaging combination of presentations, exercise-based and group activities the course covers the latest in statistical methods, as well as how and where to apply them. The practical hands-on sessions use real-world longitudinal data, from the Household, Income and Labour Dynamics in Australia (HILDA) longitudinal survey, and Growing up in Australia: The Longitudinal Survey of Australian Children (LSAC).

    When: 9 - 13 December 2019, 9am – 5pm

    Location: UQ's Institute for Social Science Research, Cycad Building, 80 Meiers Road, Indooroopilly

    For more information please click here

    • 10 Dec 2019
    • 6:00 PM - 7:15 PM
    • Old Geology Lecture Theatre 1, University of Melbourne, Parkville

    Initiatives to increase the diversity of the statistics and mathematics workforce are flourishing around Australia and around the world: but what impact do these initiatives have? In this event, we will talk to some of the women leading initiatives to increase the representation of women in stats and maths. Join us for an evening of discussion around why diversity is important, what some of the barriers to women’s equal participation in STEM fields are, what is being done to break these barriers down, and what you can do.

    A panel discussion will follow a series of short talks:

    After the event we will be going to the Prince Alfred Rooftop and Bar for dinner and to continue the conversation. Everyone is welcome to join, however food and drinks will be at your own expense. Current SSA members will receive a free refreshment!
    • 11 Dec 2019
    • 13 Dec 2019
    • Carslaw, The University of Sydney

    Find more about the rOpenSci OzUnconf at

    • 22 Jun 2020
    • 26 Jun 2020
    • Sydney

    This is the first time ISEC will be held in the Southern Hemisphere! Sydney is home to the Sydney Opera House, Bondi Beach, the Tim Tam, half-decent weather even in winter, and it will be whale season...

    Confirmed plenary speakers:

    - Christl Donnelly (Imperial College, London)
    - David Borchers (St Andrews)
    - Di Cook (Monash)
    - Kiona Ogle (Northern Arizona)
    - Mark Bravington (CSIRO)

    Invited sessions on:

    - Reproducible Science
    - Methods for high throughput community data
    For more details go to

    There will be a Skills Showcase the day before the conference, with introductory tutorials running in parallel on a diverse range of topics, including Spatial Capture-recapture, Learning Python, Disease modelling and more. As usual, there will be short courses in the days before the conference.

    • 5 Jul 2020
    • 10 Jul 2020
    • Seoul, Korea

    The International Program Committee (IPC) of the International Biometric Society’s (IBS) 30thInternational Biometric Conference (IBC2020) calls for Invited Session proposals. IBC2020 will be held 5-10 July 2020 at the COEX (Convention & Exhibition Center), Seoul, Korea.

    • 6 Jul 2020
    • 8:00 AM
    • 10 Jul 2020
    • 6:00 PM
    • Gold Coast Convention Centre, 2684 -2690 Gold Coast Highway, Broadbeach, QLD

    Welcome to the ANZSC 2020 Conference

    The organising committee warmly invites you to the 2020 Australian and New Zealand Statistical Conference, which will take place on the Gold Coast from the 6th to the 10th of July 2020.

    This conference brings together four leading statistical communities in the region – the Statistical Society of Australia, the New Zealand Statistical Association, the International Institute of Business Analysis (Special Interest Group for Business Analytics), and the Australian Conference on Teaching Statistics.

    The aim of this conference is to bring together a broad range of researchers and practitioners across a variety of statistical disciplines to facilitate the exchange of theory, methods and applications.

    With these four societies working together there will be strong program components of interest to a wide diversity of academic, government, and industry colleagues. This includes the full spectrum of delegates from those advancing theoretical methodology to those working on industry applications (in traditional and non-traditional statistical areas). Of particular interest is how Big Data continues to impact all of us.

    Information on Keynote Speakers and the Conference program will be available shortly so watch this space for updates.

    The conference will be held at the Gold Coast Convention and Exhibition Centre (GCCEC) situated in the heart of the Gold Coast. From GCCEC, Surfers Paradise (the social hub of the Gold Coast) is 5km to the North, the Star Casino and Pacific Fair are immediately to the South (the largest regional shopping and dining destination in Queensland), the beach (Broadbeach) is just ten minutes walk, and the Broadbeach restaurant complex is immediately to the East (short 5 minutes walk). Social tours can easily be made to the rainforest (such as Tambourine National Park and World Heritage-listed Lamington National Park), to places of Aboriginal Indigenous significance, to Stradbroke Island, and to Australia’s greatest theme parks.

    ANZSC2020 promises to be a truly amazing experience on both a professional and a social level.

    Please check out the official conference website and register your interest here.

    We look forward to seeing you on the Gold Coast in 2020!

    • 11 Jul 2021
    • 15 Jul 2021
    • The Hague, The Netherlands

    The 63rd ISI World Statistics Congress will bring together statisticians and data scientists from academia, official statistics, health sector and business, junior and senior professionals, in an inviting environment.

    The inspiring and interactive programme will provide the platform to learn about the latest developments in statistical research and practice in an informal ambiance. A series of short courses, satellites and other events completes the WSC programme.

    • 27 Jun 2022
    • 1 Jul 2022
    • Darwin, Australia

    The inaugural

    Joint Southern Statistical Meetings 2022

    will be held in Darwin from 27 June – 1 July 2022.

    This conference will bring together the leading statistical communities in the region to provide a forum for researchers and practitioners across a variety of statistical disciplines to facilitate the exchange of theory, methods and applications.

    To be kept up to date with our conference planning, please email your details to

    We invite regional associations to contact us with expressions of interest to be part of this event. If you would like to sponsor JSSM2022 please get in touch as well.

    See you in Darwin in 2022! 

    • 6 Jul 2022
    • 14 Jul 2022
    • St Petersburg, Russia

    The ICM 2022 (International Congress of Mathematicians) will take place 6–14 July 2022 in St. Petersburg, Russia.

    The 19th General Assembly of the IMU will be held in St. Petersburg, on 3–4 July 2022. 
    The official website of the Congress is

    • 10 Jul 2022
    • 15 Jul 2022
    • Riga, Latvia

    to be held at the Radisson Blu Latvija Conference & Spa Hotel

Past events

13 Nov 2019 NSW Branch: Annual Dinner
13 Nov 2019 NSW Branch: Annual Lecture by Prof Ian Marschner
13 Nov 2019 NSW Branch: J. B. Douglas Awards
13 Nov 2019 UQ Institute for Social Science Research: Essential Social Analysis Skills Course - external event
13 Nov 2019 NSW Branch: J.B. Douglas Awards Sponsorship
12 Nov 2019 WA Branch meeting: Prof Cathryn Lewis – Hansford-Miller Fellow 2019
12 Nov 2019 Time Series & Forecasting Symposium (TSF2019), Sydney - external event
8 Nov 2019 UQ Institute for Social Science Research: Program Evaluation Course
7 Nov 2019 Statistical Design and Analysis in Data Science - external event
7 Nov 2019 Statistical Design and Analysis in Data Science - external event
5 Nov 2019 WA Branch Young Statisticians: Meet up with Professor Cathryn Lewis (2019 Frank Hansford-Miller Fellow)
5 Nov 2019 Queensland Branch meeting - November
4 Nov 2019 CPD97- Network meta-analysis and population adjustment for decision-making - CPD97
31 Oct 2019 Vic Branch – Belz Dinner
31 Oct 2019 Vic Branch – Statistics is the Crown Jewel of Data Science (Belz Lecture)
28 Oct 2019 Webinar: An introduction to business analytics beyond statistical analysis
23 Oct 2019 SA Branch Meeting: Dr David Baird VSN NZ Ltd
21 Oct 2019 NSW Branch: October Event by Prof Elizabeth Stuart
21 Oct 2019 B&B Networking Event
21 Oct 2019 CPD105 - Propensity score methods for estimating causal effects in non-experimental studies: The why, what, and how
9 Oct 2019 SSA NSW Young Statisticians & Data Scientist Careers Networking
8 Oct 2019 WA Branch: Displaying Uncertainty and Risk - Dr John Henstridge
3 Oct 2019 Randomization, Bootstrap and Monte Carlo Methods in Biology - external event
1 Oct 2019 SSA-Event: YSC2019 Dinner - Kingston Hotel
1 Oct 2019 Queensland branch meeting: Automated Technologies for Systematic Review & Meta-Analysis
1 Oct 2019 SSA-Event: Young Statisticians Conference 2019
30 Sep 2019 CPD102 - SSA Canberra/YSC Event: Pre-Conference Trivia Night!
30 Sep 2019 CPD101- Mediation Analysis Using Potential Outcome Framework
30 Sep 2019 CPD103 - Maximising the use of Australian Bureau of Statistics Data Products and Analysis Tools
30 Sep 2019 CPD98- Communicating with R Markdown
26 Sep 2019 SA Branch Meeting: Peter Kasprzak
24 Sep 2019 Vic Branch – Young Statisticians Showcase 2019
24 Sep 2019 NSW Branch: A notion of depth for curve data by Dr Pierre Lafaye de Micheaux
23 Sep 2019 CPD106- Advanced R skills: Introduction to Shiny and Building R Packages
17 Sep 2019 SSA Webinar with Noel Cressie: Inference for Spatio-Temporal Changes of Arctic Sea Ice.
10 Sep 2019 WA Branch Meeting - Matt Schneider
5 Sep 2019 Applied Statistics and Policy Analysis Conference, 2019 - external event
3 Sep 2019 Queensland Branch meeting: Shiny showcase
28 Aug 2019 SA Branch Meeting - Dr Kathy Haskard
27 Aug 2019 Vic Branch – Detecting botnet activity using machine learning
20 Aug 2019 Talk on the QUT Digital Observatory
19 Aug 2019 Oceania Stata Conference - external event
18 Aug 2019 ISI 2019 – 62nd ISI World Statistics Congress - external event
13 Aug 2019 WA Branch Meeting - Joint IBS and SSA - Suman Rakshit
7 Aug 2019 SA Young Statisticians' Career Event
7 Aug 2019 2019 International Conference and Workshops on Survey Research Methodology - external event
6 Aug 2019 NSW Branch: Gender and Cultural Bias In Student Evaluations of Teaching at Universities by A/Prof Yanan Fan
24 Jul 2019 SA Branch Meeting - Dr Murthy N Mittinty
24 Jul 2019 The Research School on Statistics and Data Science 2019 (RSSDS2019) - external event
18 Jul 2019 Vic Branch - Tutorial on sequential Monte Carlo methods in statistics
18 Jul 2019 Minitab Insights Event Australia - external event
17 Jul 2019 Statistical Tools for the Pharmaceutical Industry - external event
9 Jul 2019 (Cancelled) WA Branch Meeting
9 Jul 2019 SSA-QLD Career Seminar: Lead With Statistics
7 Jul 2019 34th International Workshop on Statistical Modelling (IWSM2019) - external event
4 Jul 2019 Gaining skills in biostatistical consultancy- CPD94
3 Jul 2019 R skills workshops: R Markdown and Building R packages
2 Jul 2019 Tutorial on Sequential Monte Carlo methods in Statistics
1 Jul 2019 Computational and Applied Statistics (CAS 2019) - external event
30 Jun 2019 42nd Mathematics Education Research Group of Australasia (MERGA) Conference 2019 - external event
28 Jun 2019 Semiparametric regression with R - CPD99
26 Jun 2019 SA Meetup event: What went wrong with the polls? Do statisticians have a role to play?
25 Jun 2019 Vic Branch - Mentoring Breakfast
19 Jun 2019 Systematic reviews & meta-analysis of prognosis studies
11 Jun 2019 WA Branch Meeting - Dr Adriano Polpo - Hypothesis Tests: Using Adaptive Significance Levels for Decisions
11 Jun 2019 Data science helping to create a better justice system - an ACEMS Public Lecture at UTS
29 May 2019 SA Branch Meeting - Dr Beben Benyamin & Dr Ang Zhou
28 May 2019 Vic Branch – A recipe for quantifying the impact of prevention
28 May 2019 ICORS-LACSC 2019 - external event
16 May 2019 Fast algorithms and modern visualisations for feature selection - CPD96
14 May 2019 WA Branch Meeting - Young Statisticians Meeting
7 May 2019 QLD branch - Multimorbidity: Measurement for Health related Quality of Life and Health service use
7 May 2019 Chief Data & Analytics Officer Exchange - external event
4 May 2019 Data Day- Melbourne - external event
2 May 2019 Data Day- Sydney - external event
30 Apr 2019 Vic Branch – Reproducibility and Open Science
29 Apr 2019 Spatio-Temporal Statistics with R
17 Apr 2019 SA Branch Meeting - Professor Michael Sorich
9 Apr 2019 WA Branch Meeting - Prof Inge Koch
19 Mar 2019 Vic Branch – AGM + Statistics with industry: demonstrating impact
11 Dec 2018 Queensland Xmas Party
26 Sep 2018 Young Statisticians’ Workshop 2018
25 Sep 2018 Urban Modelling and Understanding with Machine Learning
11 Sep 2018 Young Statistician Careers Seminar
5 Sep 2018 Workshop: Semiparametric Regression with R with Matt Wand
28 Aug 2018 SSA Biostatistics Networking Event
26 Aug 2018 International Society for Clinical Biostatistics and Australian Statistical Conference 2018

Join us

SSA is the home for professionals working in statistics. A place where you belong, connect with others, advance your career and feel inspired.

Our core purpose is to connect you with great people and great opportunities, so you can be successful in your current role and with your career aspirations.

Join now

Powered by Wild Apricot Membership Software