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To have your event added to this list, please forward the event details, including url, to our Events Coordinator Jodi Phillips.

Upcoming events

    • 28 Mar 2023
    • 5:15 PM - 6:00 PM (AEDT)
    • Staff Tea Room, Peter Hall Building, The University of Melbourne, 813 Swanston St, Parkville VIC 3052 OR Online via Zoom

    SSA Vic branch members are invited to join us for our Annual General Meeting.

    For the agenda click here

    To read the proposal to change the name of the branch click here

    To read the proposal to amend the rules to expand the number of council positions click here

    For the minutes of the last AGM click here

    For the annual report click here

    For members who are unable to attend, you are welcome to email and nominate another member to vote on your behalf.

    Following the conclusion of the AGM we will be hearing from Professor Gordon Smyth for our March event, titled "20 years of statistical bioinformatics: a brief history of the limma and edgeR packages". To register for this talk and to find out more visit the event page.

    • 28 Mar 2023
    • 5:15 PM - 7:00 PM (AEDT)
    • Hybrid (in-person and on Zoom)

    SSA Canberra invites you to its AGM and March branch meeting of 2023, which will feature Sumonkanti Das, Bernard Baffour and Alice Richardson, Statistical Support Network from ANU present present in-person (+streamed online) on the Estimation of daily smoking prevalence for disaggregated statistical areas in Australia.

    The Annual General Meeting of the SSA Canberra Branch will be held in hybrid format, both in person at ANU and by zoom, at 5.15pm Tuesday 28 March. All relevant documents; proxy form, Council nomination form, Annual Report, Financial and Membership reports, are on or will soon be loaded to the google drive SSA Canberra Branch AGM documents. The talk featuring Sumon, Benard and Alice will take place immediately after the AGM around 6pm. After the talk, there will an opportunity for those interested to attend a dinner with speakers. Please see below for more details!

    Time: 5:15pm – 6:00pm AEDT (AGM) and 6.00pm – 7.00pm (talk)   


    Venue: Lecture Theatre 1, HW Arndt Building, Building 25A, Kingsley Place, ANU (opposite the CBE Building), or via Zoom. Please see the bottom of this event page for Zoom links.

    Note: For in person attendees, the front doors of the Arndt Building lock at 6:15pm so attendees will need to be in before then and they will need to be swiped out afterwards by an ANU attendee.


    Dinner: After the talk we will be holding a dinner at Rice Tapas, Level 2/24 Garema Pl, Canberra. (RICE THAI TAPAS RESTAURANT, Canberra - Menu, Prices & Restaurant Reviews - Tripadvisor)  If you are interested in attending the dinner, please let me know by 5pm Monday 27 March by entering your details at attendance sheetor contacting me (; 0407 916 868). Please regard this as a firm commitment, not just an intention. For withdrawals after the deadline, please remove your name from the sheet and phone or text me (0407 916 868).

    NOTE: We are offering discounts to SSA Early Career and Student members who attend dinner! Specifically, dinners will be a fixed charge of $10 for student members and $20 for early career members. Others will pay their share of the bill, after SSA applies a small subsidy. Typically this is $30-$40. Please bring cash if possible."

    Talk details

    Speakers: Sumonkanti Das and Bernard Baffour, School of Demography ANU, and Alice Richardson, Statistical Support Network, ANU

    Abstract: Official statistics on health outcomes for small domains are highly prized by policymakers and re searchers alike, for measuring and monitoring progress of communities towards healthy lifestyles. Countries like Australia use their National Health Survey to monitor adult health behaviours such as daily smoking. However, the national level health survey data can not be used to estimate accurate daily smoking prevalence at the disaggregated statistical area (SA) level due to lack of information. This NHMRC-funded study aims to estimate the prevalence of daily smoking at SA levels 3 and 4. 

    Direct estimates of daily smoking and their smoothed standard errors for the domains at SA3 level have been used as input for developing multilevel models, which are expressed in a hierar chical Bayesian framework and fitted by Markov Chain Monte Carlo (MCMC) simulation. The developed models provide consistent estimates at the most detailed level domains by borrowing cross-sectional and spatial strengths. The detailed level domain predictions are then aggregated to obtain estimates at higher aggregation levels. Lower-level prevalences and their standard errors are plotted in a bivariate choropleth map, which permits simultaneous exploration of the spatial distribution and its accuracy.

    The performance of the model-based estimates are compared with the corresponding design-based direct estimates. Significant inequalities within and between the SA3s are investigated to look for patterns that suggest policy actions that can be applied at either aggregated or disaggregated domains. These findings can help health researchers and policymakers to deliver programs to the most vulnerable, enabling them to meet their health goals in a timely way.


    Alice Richardson has been working as the Lead of the Statistical Support Network (formerly Director of the Statistical Consulting Unit) at Australian National University (ANU) since October 2019. Before this position, she worked as Biostatistician at the National Centre for Epidemiology & Population Health at ANU and at the University of Canberra. Her PhD on the statistical properties of robust methods of estimation for multilevel linear models was also from ANU. Her research interests are in linear models and robust statistics; statistical properties of data mining methods; applications of statistical methods to large data sets especially in population health and the biomedical sciences; and innovation in statistics education. She is the Principal Investigator of the NHMRC Idea Grants on “Filling in the blanks: a spatial visualisation tool to align national health outcome data with regional health policy objectives”.

    Bernard Baffour is an Associate Professor in the School of Demography at ANU. He is also the Secondary Investigator on the NHMRC Idea Grant “Filling in the blanks”. He completed his PhD in social statistics from the University of Southampton in the United Kingdom, where he investigated the statistical properties of triple system capture-recapture estimators in population censuses; and subsequently undertook a post-doctoral fellowship examining the relationship between weather and health, through quantifying the impact drops in temperature had on hospital admissions. Prior to joining at the ANU in 2017, he was a Research Fellow in Social Statistics at the Institute for Social Science Research at the University of Queensland from 2012. He has a diverse range of experience across a wide spectrum of disciplines from education, sociology, epidemiology, public health to operational research.

    Sumonkanti Das has been working as Research Fellow in the School of Demography at ANU since 2020, dedicating most of his time to the NHMRC Ideas Grant “Filling in the blanks”. He completed his PhD from the University of Wollongong in the area of small area estimation (SAE) focusing on robust inference in poverty mapping with a particular interest in developing countries. After his PhD, he worked as a post-doctoral researcher in the Quantitative Economics department at Maastricht University in the Netherlands. He worked on multilevel time series modelling to estimate mobility trends for small domains of the Dutch population by accounting for survey redesigns. Before joining Maastricht University, he was affiliated as a faculty member of the Department of Statistics, Shahjalal University of Science and Technology in Bangladesh. He has an immense interest in implementation of SAE methodology in the field of population health, nutrition, demography, and poverty. He also has expertise in multilevel modelling of complex survey data.


    Topic: SSA Canberra AGM + Talk, 28 March 2023

    Time: Mar 28, 2023 05:00 PM Canberra, Melbourne, Sydney

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    • 28 Mar 2023
    • 6:10 PM - 7:10 PM (AEDT)
    • Evan Williams Theatre, Peter Hall Building, The University of Melbourne, 813 Swanston St, Parkville VIC 3052 OR Online via Zoom

    Join the Vic branch for our post-AGM talk as we hear from Professor Gordon Smyth


    Genomic technologies underpin modern biomedical research. These technologies produce data that is hugely multidimensional. Statistical thinking is highly relevant but classic univariate statistical methods can perform poorly in the high dimensional context. The limma and edgeR software packages were developed for analysing gene expression data from microarray and RNA-seq technologies. This talk will give a brief historical perspective on the packages and a discussion of some of the ideas that made them successful.


    Gordon has a PhD in mathematical statistics from the Australian National University. For 15 years, he was an academic in mathematics and statistics departments at the University of California, the University of Southern Denmark, the US Naval Postgraduate School and the University of Queensland. His research interests were in statistical modelling and statistical computing and he wrote a textbook on generalized linear models. Excited by the possibilities of the genomic era, he made the decision to move to the WEHI in 2001 to apply his skills to the new discipline of statistical bioinformatics. At the WEHI, Gordon pioneered the use of linear models, empirical Bayes and generalized linear models for modelling gene expression data from high-throughput genomic technologies. He and his Lab created what are still the world's most downloaded R packages for microarray and RNA-seq data analysis. He is currently Head of WEHI's Bioinformatics Division.

    • 29 Mar 2023
    • 5:00 PM - 7:00 PM
    • GP-P-419, P Block, Gardens Point Campus, QUT


    5:00PM, WEDNESDAY 29th March 2023

    VENUE:  GP-P-419, P Block, Gardens Point Campus, QUT/Zoom

    Please join us in-person/online for the Queensland Branch AGM, on the 29th of March. The AGM will start at 5:00pm, with the seminar starting at 6:00pm at the same venue. For those who are unable attend in person, a Zoom link will be sent with registration.


    1. Welcome: apologies and proxies
    2. Minutes of the 2022 Annual General Meeting
    3. Matters arising from the Minutes of the 2022 Annual General Meeting
    4. Reports
      • President's Report
      • Treasurer's Report
    5. Election of Office Bearers
      • Election of President
      • Election of Secretary
      • Election of Treasurer
      • Election of Councillors
    6. Appointment of Honorary Auditor
    7. Any Other Business
    8. Seminar (at 6:00 pm)
    Please find details for the seminar below.

    Title: Understanding the interpretation and presentation of statistical methods in the Australian criminal justice system.

    Abstract: Lani's PhD thesis (currently under examination) delves into how statistical evidence is presented in the Australian criminal justice system, examining how potential jurors and expert witnesses understand and present this evidence. In this presentation, Lani will provide valuable insights into the complexities of presenting statistical evidence in legal settings, highlight ways in which experts can assist in optimising lay comprehension, and discuss factors that may impact a potential juror's understanding of statistical evidence.

     Presenter: Lani Cronin

    Lani is a graduate data scientist with a strong background in forensic applications of statistics and presenting them to both lay and expert audiences. As part of Aurizon's Careers in Action program, Lani works in a team of data scientists focused on building commercial-scale machine learning models for the management and maintenance of rail network assets.


    Nominations are called for the positions of President, Secretary, Treasurer and members of Branch Council for 2023 in accordance with Rule 12b of the Branch. Nominations should be received, in writing, by the Secretary, on or before Wednesday 29th of March 2023. Such nominations shall be signed by at least two members, and shall be accompanied by the candidate's written statement of willingness to stand. Nomination forms will also be provided at the AGM. Separate nomination forms are available for councillors and executive positions (President/Secretary/Treasurer).

    Please scan and email written nominations to: or (SSA-QLD branch secretary: Adrian Barnett).

    • 30 Mar 2023
    • (AEDT)
    • 31 Mar 2023
    • (AEDT)
    • Online

    The Research Society is offer this workshop: Fundamentals of Qualitative Research.

    This course provides an introduction to Qualitative Research.

    Learning Objectives

    In this course you will learn how to:

    • Recognise when conducting qualitative research is appropriate
    • Understand the logistics involved in running a qualitative project
    • Describe the differences between the main types of qualitative data collection: namely focus groups, in-depth interviews, observation, online qual etc
    • Understand the role of the moderator/ interviewer and how to create the right environment for respondents
    • Learn different approaches to eliciting unbiased responses
    • Learn different tools for handling challenging situations during interviews
    • Understand why getting below the surface of respondent behaviour is important
    • Understand the process of analysis and report writing for qualitative research.

    Day 1: 30 March 12 noon - 4 pm

    An introduction to Qualitative research

    • What is qualitative research?
    • Why conduct qualitative research?

    When to use Qualitative research and overview of the different qualitative methods

    • Strengths and weaknesses of qualitative and quantitative research. When is each appropriate?
    • Qual design considerations in thinking about data collection options available.

    The basics of Qualitative moderation

    • The role of the discussion guide, basics of moderating groups and depth interviews.
    • Group dynamics and avoiding bias in qualitative situations.

    Day 2: 31 March 12 noon - 4 pm

    Projective techniques in Qualitative Research

    When to use stimulus. Projective techniques – how to use and not abuse, practical uses of projective techniques in qualitative projects.

    Analysis of qualitative information and report writing

    Putting it all together – interpretation – presentation and practical examples of how to draw conclusions from qualitative data.

    An introduction to professional standards and the Research Society Code of Professional Behaviour


    Nicky Fraser

    A constant fascination for what makes people tick led to a Masters in Social Behaviour at LSE, including Consumer Psychology and Psychology of Advertising, where I first encountered qualitative research. Later pursued this interest further, training in psychotherapy.

    Over 27 years research experience, spanning UK and Australia, with a few side trips along the way!

    National and international expertise across a wide range of categories and markets, working for some of the leading research agencies in Sydney and London. Still called on when leading global agencies need extra resource for large blue chip clients

    Breadth of experience covers the full range of categories including FMCG, Services and Social, with audiences from kids and teens through to bankers and CEO’s

    Alison Dexter

    Ali has 30+ years of research and consulting experience and has worked locally and globally in the UK, Asia, US.

    Ali began her career in a management consultancy in London which led to a job back in Sydney with a strategic marketing consultancy. That company was bought by a global research company and off Ali went to Hong Kong for 4 and a half years, feeling extremely lucky that the world of market research enabled working in different places (this pattern was to repeat for Vietnam, New York, Sydney, Melbourne).

    Ali studied Psychology, Anthropology and English lit in her university degree, whilst being very fortunate to have some wonderful teachers in the Market Research and Psychology world, that fuelled her love of qual.

    Ali is passionate about leveraging new techniques, technology and different thinking to get as close to the truth of human behaviour as possible.

    30th Mar 23 12:00 PM to 4:00 PM
    31st Mar 23 12:00 PM to 4:00 PM

    Start Time:
    NSW | ACT | VIC | TAS: 12 noon - 4:00 pm
    QLD: 11:00 am - 3:00 pm
    SA: 11:30 am - 3:30 pm
    NT: 10:30 am - 2:30 pm
    WA: 9:00 am - 1:00 pm

    Arrival Time:
    10 min before start time

    your device online

    Member Price: AU $ 250.00

    Non-member Price: AU $ 750

    To register click:

    • 30 Mar 2023
    • 2:00 PM (AEDT)
    • Online

    ECSSN SSA and NZSA Joint Webinar Series: Academia vs Industry: A statistical viewpoint

    Time: 2 pm AEDT and 4:00 pm NZDT.

    Statistics is a skill that is essential for progress in multiple environments. In academia, we apply these skills to understanding measurements produced in research. In industry, these skills are required to make sound decisions based on the best available information. However, the mindset needed to approach problem-solving in these sectors has many subtle and sometimes not-so-subtle differences.

    In this talk, she will discuss, based on her personal experience, aspects of academia and industry that differ and the pros and cons for each. This will include the level of statistical difficulty, biased perceptions between workers in each sector, timeframes, technology, extraneous responsibilities, communication, teams and administration.


    Dr Clair Alston-Knox, Senior Statistician, Head of Visualisation Development and Statistical Modelling, Predictive Analytics Group

    Clair began her career as an applied statistician with NSW Agriculture as a biometrician at a remote location. After completing a Master of Science (Research) in the area of longitudinal analysis of Poisson data and Generalised linear models, she left this position to study for a PhD in using Bayesian Mixture Models to analyse sheep CT images. The research question driving this thesis aimed to maximise the information available to livestock managers to make decisions for drought management.

    After completing her PhD, she worked as an academic in applied statistics, specifically, Bayesian analysis, for several years at QUT and Griffith University. At Griffith, exposure to a wide range of social and behavioural science research lead to her desire to take up her current industry role, which combines industry consulting, research and software development. A recent highlight of this role has been working with a team that obtained a Business Research and Innovation Initiative (BRII) grant to examine the feasibility of combining microwave technology and machine learning to predict asbestos presence in building materials. She is also currently collaborating with a research team at Murdoch University in the area of accreditation for new technology in predicting carcase traits. In this role, she sees a wide range of projects, including government and academic consulting, as well as maintaining research links via student supervision and early career researcher mentoring.

    • 31 Mar 2023
    • 12:30 PM - 1:30 PM (AEDT)
    • online

    Statistical Consulting Network March Meet-Up

    Come along with your thinking cap, maybe a problem, and some lunch!

    The Statistical Consulting Network invites you to their monthly meet-up, a virtual lunchtime meeting where statisticians help each other out with problems that they aren’t sure how to deal with.  This virtual meeting is held on Zoom at lunchtime on the last Friday of each month, 12:30-1:30 PM (AEDT).  We start each meet-up with announcements, or occasionally a special topic discussion, then discuss problems that attendees have brought along with them.

    If planning to share a problem, please make sure you think about how to communicate the broader context for the study (What is the research question? How were data collected?), not just the part of it you are unsure about.  If the problem relates to data properties and model-fitting then it might help to bring along some exploratory analyses.  Please consider whether you need permission from your client to share these details, and obtain any relevant permissions from them.

    We also have a Slack workspace where members of the consulting network can communicate between meetings, or post problems or relevant materials they would like to discuss during a meeting.

    Friday 31th March, 12:30-1:30 PM (AEDT).

    Zoom link:

    Slack Workspace link:
    • 18 Apr 2023
    • 6:00 PM - 7:00 PM (AWST)
    • Cheryl Praeger Lecture Room, The University of Western Australia

    The Frank Hansford-Miller Fellowship subcommittee of the WA Branch of the Statistical Society of Australia (SSA) is pleased to announce that the Fellow for 2023 is Professor Guy Nason of Imperial College London.

    Professor Nason will be delivering his lecture at our April gathering and has requested that this event be in-person only without online streaming.

    Further information on the Fellowship is available here.

    Date: Tuesday, 18 April 2023.
    Time: 6:00PM.
    Location: Cheryl Praeger Lecture Room, The University of Western Australia.

    NB: this event is on the third Tuesday rather than the second Tuesday of the calendar month which is typical of regular SSA WA gatherings.

    Network Time Series

    Professor Guy Nason, Imperial College London.

    A network time series is a multivariate time series where the individual series are known to be linked by some underlying network structure. Sometimes this network is real and known beforehand, but sometimes one assumes an unknown virtual network and tries to infer it along with the modelling.

    Network time series are becoming increasingly common, long and collected over a massive number of variables. There are many variants including network time series whose underlying network changes over time, multiple network time series, series with different link types, antagonistic network time series, count data series to name but a few.

    This talk advertises some recent methods for the modelling and fitting of network time series, pros and cons and, in some circumstances, attractive forecasting performance. We plan to show examples from epidemiology and economics, sometimes both together.

    About the Speaker

    Guy Nason is Chair in Statistics at Imperial College London. He has undertaken research in the areas of wavelets and time series analysis, particularly in the area of non-stationary time series.

    A major current research direction is network time series in which he is involved in the NeSTProgramme Grant - a partnership of nine investigators at the six UK universities of Bath, Bristol, LSE, Oxford, York and Imperial. He is particularly interested in the statistical modelling of wine production and is especially interested in modelling the wines of Western Australia.

    Refreshments and Dinner

    Members and visitors are invited to mingle over wine and cheese from 5:30PM onwards at the venue.

    Following the meeting all are invited to join the Fellow for dinner at a nearby restaurant. Visitors are welcome.

    Venue Directions

    The Cheryl Praeger Lecture Room is located on the ground floor of the Mathematics building at The University of Western Australia. Its entrance is on the northern side of the building. See: UWA Maps, Google Maps.

    Parking is free on the UWA Crawley campus after 5:00PM. A convenient place to park is Car Park 18 accessible from Fairway Entry 1.

    For further information please contact the WA Branch Secretary (
    • 20 Apr 2023
    • 9:00 AM - 5:00 PM (AEST)
    • ): Room 163, 14 Sir Christopher Ondaatje Ave Macquarie University, NSW 2109, Australia
    • 78

    The NSW Branch and School of Mathematical and Physical Sciences, Macquarie University is offering this workshop: Mathematical Engineering of Deep Learning - Part One Foundations

    In this workshop, we first present the general feed-forward deep neural network. After exploring the expressive power of deep neural networks, we dive into the details of training by understanding the back-propagation algorithm for gradient evaluation and exploring other practical aspects such as weight initialisation, dropout, and batch normalization.

    The second part of the workshop concentrates on convolutional neural networks. Much of the success of deep learning is due to the strength of convolutional neural networks when applied to images and similar data formats. The concepts of channels and filter design are introduced, followed by an exploration of the common state of the art architectures that have made significant impacts and are still in use today.

    The last part of this workshop is about sequence models.  These models are critical for data such as text with applications in natural language processing. We explore recurrent neural networks and their generalizations. These include long short-term memory models, gated recurrent units, auto-encoders for end-to-end language translation, and the attention model with transformers. The workshop includes deep learning demonstrations using R and Python software.

    Course Outline

    • -        The General Fully Connected Architecture
    • -        The Expressive Power of Neural Networks
    • -        Activation Function Alternatives
    • -        The Back Propagation Algorithm
    • -        Weight Initilization and Batch Normalization
    • -        Mitigating Overfitting with Dropout and Regularization
    • -        Overview of Convolutional Neural Networks
    • -        The Convolution Operation
    • -        Building a Convolutional Layer
    • -        Building a Convolutional Neural
    • -        Inception, Resnets, and Other Landmark Architectures
    • -        Recurrent Neural
    • -        Long Short Term Memory Models
    • -        Gated Recurrent Unit Models
    • -        Encoder-decoder for End to End Translation
    • -        Transformers Model

    Prof. Benoit Liquet-Weiland and Dr Sarat Moka

    Dr Liquet is a Professor of Mathematical and Computational Statistics at Macquarie University in the School of Mathematics and Statistics. In addition, he is affiliated to the University of Queensland and to the Université de Pau et Pays de l’Adour (UPPA). He was previously affiliated with ACEMS (Centre of Excellence for Mathematical and Statistical Frontiers), Queensland University of Technology. Throughout his career he has extensively worked in developing novel statistical models mainly to provide novel tools to analyse clinical, health and biological data arising from epidemiological studies. Since 2011, he moved to the field of computational biology and generalised some of these methods so that they scale to high throughput (“omic”) data.  He has been teaching an advanced course on the mathematical engineering of Deep Learning at the Australian Mathematical Sciences Institute (AMSI) summer school in 2021.  A book draft of his new co-authored book on concepts of “Deep Learning” is available at . Benoit Liquet works on Applied Statistics, as well as on the development of R packages and on industrial applications (such as Machine Learning). 

    Dr Sarat Moka is a new Lecturer at the School of Mathematics and Statistics at UNSW. He was previously Research Fellow at the School of Mathematical and Physical Sciences, Macquarie University and an ACEMS (ARC Centre for Excellence for Mathematical & Statistical Frontiers) Postdoc at The University of Queensland. He has obtained a PhD in Applied Probability from Tata Institute of Fundamental Research, Mumbai, and Master of Engineering from the Indian Institute of Science, Bengaluru. He has been working on problems in Statistics, Applied Probability, and Deep Learning. In addition, he has worked on the modelling of cancer data and on the Safe Blues project (  He has been teaching advanced courses in Statistics and Deep Learning and is currently co-writing a book on "The Mathematical Engineering of Deep Learning" (

    Course Timetable (including morning tea, lunchtime and afternoon tea breaks)

    Below is the tentative schedule for the workshop; it will be adapted on the workshop day.


    9:00 – 10:45

    Session 1

    10:45 – 11:15 (30 mins)

    Morning tea break

    11:15 – 12:45

    Session 2

    12:45– 13:45 (1 hour)

    Lunch Break

    13:45 – 15:15

    Session 3

    15:15 – 15:45 (30 mins)

    Afternoon tea break

    15:45 – 17:00

    Session 4


    Target Audience: From engineering, signal processing, statistics, physics, econometrics, operations research, quantitative management, pure mathematics, bioinformatics, applied machine learning, or even applied deep learning.


    Delegates are required to bring their own laptop and have R, Rstudio, Python, and Jupyter (via Anaconda)

    Cancellation Policy:

    Cancellations received prior to Friday,14th April, will be refunded, minus a $20 administration fee. From then on wards no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to

    • 24 Apr 2023
    • (AWST)
    • Little Creatures Brewery, Mews Road, Fremantle

    The WA Branch and the ECSS Network invites students and early career statisticians for a casual evening with Professor Guy Nason of Imperial College London.

    Professor Nason is visiting Perth from the UK as the recipient of the 2023 Frank Hansford-Miller Fellowship. Further information on the Fellowship is available here.

    In addition to delivering the Fellowship Lecture and a workshop, he has reserved some time to meet with those who are early in their statistical careers.

    Date: Monday, 24 April 2023.
    Time: TBC
    Location: Little Creatures Brewery, Mews Road, Fremantle.

    More details are to come.

    For further information please contact the WA Branch Secretary (

    • 27 Apr 2023
    • 9:00 AM - 5:00 PM (AWST)
    • 139 St Georges Terrace, Perth, WA
    • 21

    The WA Branch of the Statistical Society of Australia warmly invites you to a workshop on Nonstationary Time Series: Techniques and Tools, presented by Professor Guy Nason of Imperial College London, the Frank Hansford-Miller Fellow for 2023.

    Date: Thursday, 27 April 2023.
    Time: 9:00AM - 5:00PM.
    Location: Curtin 139 St Georges Terrace, 139 St Georges Tce, Perth, WA.


    This workshop covers the modelling and analysis of (second-order) nonstationary time series. That is, time series whose second-order properties (variance, autocovariance) can change over time. We will look at some models for nonstationary time series and study their controlling parameters. We will then examine methods for estimating those parameters and statistical tests that can be used to detect non-stationarity in such time series. In the second part we will look at methods for estimating local versions of the classical autocovariance and partial autocovariance, which can provide a lot of insight into the behaviour of the series over time. Finally, we will examine methods and software for forecasting such series and seeing how they compare to methods designed for stationary series. If time permits, we might examine some network time series models.


    Laptop with R installed. Attendees will be using the locits, lpacf and forecastLSW packages. The latter two packages will be available on CRAN shortly.


     Time Session
    09:00-09:30 Arrival and registration
    [Session 1] Nonstationary Time Series: Models and Tests
    Morning Tea (catered)
    [Session 2] Practical on Spectral Estimation and Tests for Nonstationarity
    Lunch (self-catered)
    [Session 3] Local Autocovariance, Local Partial Autocovariance, and Forecasting
    Afternoon Tea (catered)
    [Session 4] Practical on Session 3 topics

    About the Presenter

    Professor Nason is Chair in Statistics at Imperial College London. He has undertaken research in the areas of wavelets and time series analysis, particularly in the area of non-stationary time series. A major current research direction is network time series in which he is involved in the NeSTProgramme Grant - a partnership of nine investigators at the six UK universities of Bath, Bristol, LSE, Oxford, York and Imperial.

    Registration Information

    This workshop will be conducted as an in-person event only. The registration fee includes morning and afternoon tea.

    Student (SSA Member)
    Student (Non-SSA member*)
    SSA Member
    General Admission
    *Email proof of student status to the WA Branch Secretary to get the discount code. Alternatively, student membership of SSA is $20 p.a.

    Venue directions

    The venue is Curtin 139 St Georges Terrace located at 139 St Georges Terrace, Perth, WA 6000. The entrance is on the southern side of the building.

    Public Transport

    There are numerous bus routes along St Georges Terrace.

    You may catch the train and disembark at the Elizabeth Quay station and then walk through Brookfield Place to 139 St Georges Terrace (about 500m).

    Car Parks

    There is no on-site parking, the closest public car parks are:

    • Central Park, 152-158 St Georges Terrace, Perth.

    • His Majesty’s, 377 Murray Street, Perth.

    • Citipark (Wilson Parking), 427 Murray Street, Perth.

    • Convention Centre, 21 Mounts Bay Rd and Mitchell Freeway, Perth.


    This event is open to all but for catering purposes, registration is essential.

    Note that this is an in-person event with no hybrid or online interaction.

    For further information please contact the WA Branch Secretary (

    • 28 Apr 2023
    • 12:30 PM - 1:30 PM (AEST)
    • Online

    Statistical Consulting Network April Meet-Up

    Come along with your thinking cap, maybe a problem, and some lunch!

    The Statistical Consulting Network invites you to their monthly meet-up, a virtual lunchtime meeting where statisticians help each other out with problems that they aren’t sure how to deal with.  This virtual meeting is held on Zoom at lunchtime on the last Friday of each month, 12:30-1:30 PM (AEST).  We start each meet-up with announcements, or occasionally a special topic discussion, then discuss problems that attendees have brought along with them.

    If planning to share a problem, please make sure you think about how to communicate the broader context for the study (What is the research question? How were data collected?), not just the part of it you are unsure about.  If the problem relates to data properties and model-fitting then it might help to bring along some exploratory analyses.  Please consider whether you need permission from your client to share these details, and obtain any relevant permissions from them.

    We also have a Slack workspace where members of the consulting network can communicate between meetings, or post problems or relevant materials they would like to discuss during a meeting.

    Friday 28th April, 12:30-1:30 PM (AEST).

    Zoom link:

    Slack Workspace link:
    • 1 Jun 2023
    • (AEST)
    • 31 Oct 2024
    • (AEDT)
    • Online-weekly one hour classes-this is 6 courses offered over the next year
    Expression of interest in survey and data science courses in 202324


    Due to the high demand for the Sampling Course in 2022 and strong interest in other courses from the International Program in Survey and Data Science (IPSDS) Masters program the Social Research Centre and Statistical Society of Australia have partnered again to expand IPSDS course offerings in Australia.

    The IPSDS is a program of the University of Mannheim and the Joint Program in Survey Methodology at the University of Maryland. It is directed by Prof. Frauke Kreuter, who is professor at the Ludwig Maximilian University of Munich.

    These course offerings are motivated back the lack of Australian equivalents.

    If you are interested in the Item Nonresponse, Sampling, Big Data/Machine Learning for Surveys and/or Weighting courses please register your interest so that we can determine whether there is sufficient demand. 

    The courses to be offered in 2023–24 are:





    Item Nonresponse and Imputation

    Jun–Jul 2023 (4 weeks)

    Prof Jörg Drechsler

    Familiarity with generalised linear models and basic knowledge of R

    Sampling I

    Oct–Nov 2023 (8 weeks)

    Dr Raphael Nishimura

    A sound background in applied statistics, proficiency in mathematics, including basic algebra

    Introduction to Big Data/‌Machine Learning I

    Jan–Feb 2024 (4 weeks)

    Prof Frauke Kreuter and Prof Trent D. Buskirk

    None, but undergrad statistics background, some familiarity with regression models assumed and familiarity with R recommended

    Sampling II

    Mar–Apr 2024 (4 weeks)

    Dr Raphael Nishimura

    Sampling I or equivalent; R skills helpful

    Step-by-Step in Survey Weighting

    Mar–Apr 2024 (4 weeks)

    Dr Anna-Carolina Haensch

    Sampling I or equivalent

    Machine Learning II

    Sep–Oct 2024 (8 weeks)

    Prof Christoph Kern and Prof Trent D. Buskirk

    Machine Learning I or equivalent and basic knowledge of R

    Basic R skills can be acquired from a SSA R workshop which will be offered before the Machine Learning course or online e.g. via DataCamp or equivalent.

    All courses are conducted over 4 or 8 weeks period (depending on the course) with weekly 1 hour online classes in addition to assignments and exam assessment at the end of the course. Participants should expect pre-recorded videos, readings and exercises to be completed outside of the weekly meetings consistent with a master’s course.

    Indicative cost per course is $1,500(ex-GST) per attendee, with $1,250(ex-GST) per attendee volume discount for organisations enrolling three or more.

    We are asking for expressions of interest in these courses to ensure there is sufficient demand for the courses to run. Please register your interest or contact with any questions.

    • 20 Jun 2023
    • 5:00 PM (AEST)
    • 11 Jul 2023
    • 6:00 PM (AEST)
    • Online- weekly 1 hour live discussion with Prof. Dr. Jörg Drechlser
    • 13

    The Social Research Centre and the Statistical Society of Australia (SSA) are very proud to offer theory-based and practice-oriented learning from faculty from world’s top ranked universities, statistical agencies and businesses via the International Program in Survey and Data Science (IPSDS), a joint program of the University of Mannheim and the Joint Program in Survey Methodology at the University of Maryland.

    The program involves asynchronous learning experience (prerecorded lectures, readings) and synchronous learning experience (virtual classroom, weekly live discussions led by the instructor)

    Course objectives:
    Introduction& Missing Data Mechanisms
    Default Strategies of (Not) Dealing with Missing Data and Their Implications
    Common Misconceptions Regarding Imputation & Basic Imputation Methods
    More Advanced Imputation Methods & Multiple Imputation

    By the end of the course, participants will...

    understand why the default way of dealing with missing data as implemented in most statistical software is often problematic.

    realize that it is better not to account for the missingness instead of applying simplistic imputation methods such as mean imputation
    or last
    -observation carried forward.

    know what is meant by a missing data mechanism and understand the implication of the different mechanisms.

    be familiar with the principle ideas and concepts of multiple imputation.

    Grading will be based on:
    2 online quizzes
    2 homework assignments
    Participation in weekly meetings & engagement in discussion forums
    Final online exam

    Instructor: Prof. Dr. Jörg Drechlser

    Drechsler, Jörg | JPSM | Joint Program in Survey Methodology ...

    Prof. Dr. Jörg Drechlser is currently the head of the Department for Statistical Methods at the Institute for Employment Research, Germany; Associate Research Professor, Joint Program in Survey MethodologyUniversity of Maryland; and Honorary Professor, University of Mannheim. His research area of interest is missing data, imputation, data confidentiality

    Course dates

    Course dates: June 20th – July 11, 2023
    Weekly live sessions with instructor: Tuesdays, 5:00 pm AEST

    Early Bird Deadline
    Please book before
    April 18, 2023 to take advantage of the Early Bird Deadline.


    Familiarity with generalised linear models and basic probability theory.

    Basic knowledge of R. R training is available online, for example via DataCamp (

    Readings: pre-reading may be provided prior to course.

    • Participants will receive access data for the online course, in particular to any learning platform that may be used. The rights of use connected to the access data are personally assigned to the participant. Passing on the access data is not allowed. Also, the temporary transfer to third parties is not permitted.
    • The right to use the transmitted access data, in particular with regard to any materials or video recordings provided, can only be exercised up to a maximum of 2 months after the program end. After expiration of this 2-months period, the access data will be deleted by Mannheim Business School (MBS). Before the expiration of this period, the participant may view the respective recorded course as often as desired and without time restriction.
    • If we have reasons to believe that the participant is abusing the right of use granted to him or that there is a violation of the terms of use, MBS reserves the right to change the participant’s access data as well as to partially or completely block the access or to prohibit the further use of the digital content.

    Group bookings

    For group bookings, please email Jodi Phillips with the names, email addresses, and telephone numbers  of the participants in the group.

    Cancellation Policy

    Occasionally workshops have to be cancelled due to a lack of subscription. Early registration ensures that this will not happen.

    Cancellations received prior to six weeks before the event will be refunded, minus a $20 administration fee. Cancellations between six and two weeks prior will receive 50% back. From then onward no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to

    For any questions, please email SSA's Event Coordinator, Jodi Phillips.

    • 16 Jul 2023
    • (EDT)
    • 20 Jul 2023
    • (EDT)
    • Ottawa, Canada

    The 64th WSC 2023, to be held 16-20 July in Ottawa, Canada, will highlight the developments and contributions of statistics, statistical science, and data science in all aspects of life, particularly the well-being and welfare of people. The WSC 2023 will host talks and presentations on a wide variety of topics, with the overall goal of presenting a balanced program that provides a sense of the current state and future direction of statistics and their applications.

    The program will span the full field of statistics including academia, business, industry, government and official statistics in line with the breadth of ISI and the Associations affiliated with ISI. Topics include but are not limited to official statistics, survey statistics, environmental statistics, business and industrial applications of statistics, mathematical statistics, probability, statistics and data science, statistics education, statistical literacy, statistical computing and data visualization.

    The opening of the submission process, which is planned for March, will be announced on the congress website WSC 2023.

    General enquiries about the Scientific Programme should be directed to

    For more information please click here.

    • 17 Jul 2023
    • (CEST)
    • 21 Jul 2023
    • (CEST)
    • The Dorint-Hotel in Dortmund, Germany
    IWSM 2023-The 37th International Workshop on Statistical Modelling

    Scientific Programme

    The IWSM 2023 programme is currently in the planning stage and will be announced here as soon as it is fixed

    Keynote Speakers

    • Gillian Heller (AUS, University Sydney)
    • Simon Wood (UK, University Edinburgh)
    • Maria Iannario (ITA, University Naples)
    • Brian Reich (US, NC State University)
    • Sports Analytics group of the football team Borussia Dortmund (the speaker will be announced soon)


    The deadline for oral short paper submission has been extended to March 7th, 2023.

    The deadline for poster short paper submission is March 31st, 2023.

    Details for submissions are available on

    • 18 Jul 2023
    • (MDT)
    • 21 Jul 2023
    • (MDT)
    • University of Colorado Boulder, USA

    Welcome to the 6th Spatial Statistics conference, which will be held at the University of Colorado Boulder, USA, from 18 - 21 July 2023 under the theme Climate and the Environment.

    The conference will provide a forum to debate and discuss how to use spatially referenced data to advance our understanding and provide support for decision making in the domain of Earth system dynamics.

    This conference will focus on climate change dynamics, their causes, their effects and their future. The conference theme will be the perspective of the Earth as a unified system with connections and feedbacks between physical and biological spheres and also human activities. Crucial developments in the methodology are in new scalable methods, spatio-temporal statistics, prediction and statistical aspects of modeling, like spatial and spatio-temporal extremes, attribution and forecasting.

    Conference Topics


    • Space-time statistics, e.g. geostatistics, point patterns, estimation methods, large dimensions
    • Spatial deep learning
    • Inverse modeling
    • Modeling of extremes
    • Stochastic geometry, tesselation, point processes, random sets
    • Causal statistical modeling
    • Trajectory/movement modeling


    • Climate system modeling and observations
    • Health e.g. epidemiology, geohealth and global health
    • Spatially-Explicit Ecological Models
    • Plant and animal epidemiology
    • Quantifying the spatial extent of hazards and risk
    • Crime and poverty mapping
    • Space/time econometrics
    • Interface of Neural Computing and Spatial/Spatio-Temporal Statistics
    • Inferring Movement and Behavior from Telemetry

    • For more information click here.

    • 19 Sep 2023
    • 20 Sep 2023
    • Concorde Hotel, Shah Alam, Malaysia

    "Empowering Statistical Science and Analytics Through Research and Innovation"

    The 6th ISM International Statistical Conference (ISM-VI 2023) is an exciting event that brings together statisticians, data scientists, researchers, and professionals from various industries to exchange ideas, knowledge, and innovations in the field of statistical science and analytics. The theme of ISM-VI 2023 is "Empowering Statistical Science and Analytics Through Research and Innovation". This theme reflects the importance of research and innovation in advancing the field of statistical science and analytics and improving decision-making in various industries.

    The conference program includes plenary sessions, keynote speeches, oral and poster presentations, and panel discussions on a wide range of topics related to statistical science and analytics. These topics include big data analytics, machine learning, data privacy and security, causal inference, Bayesian methods, and much more. Attendees will have the opportunity to learn from experts in the field and engage in discussions on the latest advancements and challenges in statistical science and analytics.

    In addition to the conference program, ISM-VI 2023 will also feature a variety of networking opportunities, including a welcome reception, a conference dinner, and an excursion. These events provide attendees with an opportunity to connect with their peers, establish new collaborations, and make lasting connections.

    ISM-VI 2023 is an excellent opportunity for professionals in the field of statistical science and analytics to keep up-to-date with the latest research and innovations, as well as to network with other professionals and build new collaborations. Attendees will leave the conference with new knowledge, ideas, and a network of professionals that they can continue to engage with in the future.

    ISM-VI 2023 is an event not to be missed for those in the field of statistical science and analytics. Register now to secure your place at this exciting event! 

    Find out more.

    • 27 Nov 2023
    • 1 Dec 2023

    The conference will be joint with SEEM at Bay Of Islands in New Zealand.

    • 4 Dec 2023
    • 8 Dec 2023
    • Melbourne

    We are pleased to announce the 2nd Bayesian Nonparametrics Networking workshop on 4-8 December 2023 to be held at Monash University ( in Melbourne, Australia. The format will largely follow the 1st of these new BNP Networking workshops that was held in Nicosia (Cyprus) in April 2022, this time with 3 mini-courses delivered by Jim Griffin, Athanasios Kottas and Stephanie van der Pas, who will also deliver Keynote talks. The workshop will also feature invited talks, contributed talks and a poster session each featuring a range of different topics presented by a blend of both junior and established researchers. Those who wish to be considered for a contributed talk or poster presentation should submit their abstract by 15 April 2023. This is the same due date for travel grant applications for junior researchers.

    For more information, please visit the workshop event page at, or contact the local organising committee via  
    • 10 Dec 2023
    • 8:00 AM (AEDT)
    • 15 Dec 2023
    • 5:00 PM (AEDT)
    • Wollongong

    The local organising committee warmly invites you to the 2023 Australian Statistical Conference (ASC) and Australian Conference on Teaching Statistics (OZCOTS), which will take place in Wollongong from the 10th to the 15th of December 2023. Save the date and register your interest now!

    The theme for the 2023 Australian Statistical Conference (ASC) is ‘Statisticians in society’, focussing on the key role statisticians play in communication across diverse areas that are key to our society.

    ASC 2023 will bring together statisticians from across Australia, as an opportunity to communicate with one another, and advance our collective knowledge of statistical methods and applications. We look forward to offering a diverse program featuring speakers from academia, government and industry across a range of disciplines and career stages. There are plans to offer some parts of the conference in a hybrid format as well. Information on Keynote Speakers and the Conference program will be available at a later date so please watch this space for updates. 

    The conference will be held at the University of Wollongong, situated in the heart of Wollongong. Wollongong is the third-largest city in New South Wales and only an hour from Sydney. Wollongong offers an escape-worthy collection of world-class beaches, playful adventures, eats, arts and iconic attractions. 

    ASC/OZCOTS 2023 promises to be a truly amazing experience on both a professional and a social level. We look forward to seeing you in Wollongong in 2023!

    For our Sponsors: The Conference provides the perfect forum for companies actively involved in the statistical community to promote their products and services. Contact us now to find out more about your sponsorship options.

    For our Exhibitors:  The Conference provides an opportunity for exhibitors to engage one on one with delegates and present videos, as well as providing a number of branding and product placement facilities.

    Check out the official conference website here.


    • 10 Dec 2023
    • 11:00 AM - 5:00 PM (AEDT)
    • Sage Hotel, Wollongong, NSW
    • 27

    Presented by Professor Sir David Spiegelhalter, University of Cambridge, A/Professor Jen Martin, University of Melbourne and Dr Linden Ashcroft, University of Melbourne

    About the workshop:
    Communication is an essential skill for statisticians who commonly need to explain complex concepts in a digestible manner to people from different disciplines. Unfortunately, few statisticians receive formal training in this area. The COVID-19 pandemic helped highlight just how important statistics is and raised the importance of clear communication. This workshop, delivered by leading figures in communication and statistical communication, will help attendees gain confidence in communicating their work and provide attendees with tips for good statistical communication.

    Presenters:        Prof. Sir David Spiegelhalter, University of Cambridge

                                  A/Prof. Jen Martin, University of Melbourne

                                  Dr Linden Ashcroft, University of Melbourne

    Cancellation Policy:

    Cancellations received prior to Friday, 1 December 2023, will be refunded, minus a $20 administration fee. From then on wards no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to

    • 10 Dec 2023
    • 11:00 AM - 5:00 PM (AEDT)
    • Sage Hotel, Wollongong, NSW and online
    • 30

    Presented by Professor Julie Simpson, University of Melbourne, A/Professor Emily Karahalios, University of Melbourne and A/Professor Karen Lamb, University of Melbourne

    About the workshop: This workshop is designed to provide participants with an understanding and tips of some of the key considerations involved in setting up and running a statistical consultancy from within a university environment:  covering a range of topics including funding and operational models, reaching and securing clients, building and funding a team, how to run consultancy projects from start to finish, managing projects, and communication skills.

    Presenters:          Prof. Julie Simps