Dear {Contact_First_Name},
It’s a wrap! While OZCOTS will continue for another day, ANZSC2021 is done and dusted!
There will be a lot of exhausted organisers and delegates tonight, but hopefully they won’t be too tired to try their skills at one of the highlights of the social program: “Would I lie to you – statistically”, at 5pm AEST. While I feel my eyes actually changed shape this week into squares, from staring at the screen for many, many hours, it was great to see so many faces and feel connected with the world again. I’m in awe of the technology used and the creativity displayed by the organisers. Just seeing the word “Elf” on the screen (by the way, thank you, Purple Elf, whoever you are, for your wonderful help today!) gave me a warm and fuzzy feeling and inspired me to push on with my family’s plans for “Christmas in July”. And while I have to confess that the statistical talks went over my head, I found out interesting things about our members, such as that SPC Co-Chair Berwin Turlach also enjoys a good Christmas in July, and that Sam Mason has a coffee machine (and obviously barista-level capabilities) that I can only dream of. Learning little snippets of information about our members like these was the real conference highlight for me.
Now bring on ECSSC2021!
Marie-Louise Rankin
Executive Officer, SSA
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Congratulations Rob J Hyndman FAA FASSA Professor of Statistics and Head of the Department of Econometrics & Business Statistics at Monash University on having been awarded the Pitman Medal 2021. |
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The Pitman Medal, a gold medal, is the society’s most prestigious award. Award recipients are recognised for a body of work that has enhanced the international standing of Australia in the discipline. The Medal commemorates Edward Pitman, Professor of Mathematics at the University of Tasmania from 1926 to 1962 and the inaugural recipient of the Medal. |
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Rob Hyndman is one of the world’s most recognised statisticians and is internationally recognised for cultivating widespread interest around forecasting. He has authored about 200 papers, chapters, or books on statistical topics since 1991. His most important contributions are in the areas of time series forecasting, forecast reconciliation, energy forecasting, and demographic fore- casting. The methodology developed in Hyndman’s research papers is used in many fields including epidemiology, demography, energy management, optometry, meteorology, operations research, pharmacology, environmetrics, tourism, ecology, satellite imaging, and chemistry. Google Scholar calculates more than 29 400 citations of his work (17 900 in the last five years). His H-index is 62. |
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Winner of EJG Pitman Prize announced! The E J G Pitman Young Statisticians Prize is awarded for the most outstanding talk by a “young statistician” at an Australian Statistical Conference. The prize is only open to members of SSA or – in the case of ANZSC2021 - to members of SSA or NZSA, and a ‘young statistician’ means a person enrolled for a degree who is studying either full-time or part-time without age limit, or a person who graduated with a Bachelor’s degree within the past five years, or a person awarded a postgraduate degree within the past year. The prize winner is selected by a committee of members of the Society appointed by Council.
Adrian Barnett commented on how difficult the selection of the winner had been, as so many deserving presentations had been seen. After thanking the panel of judges involved in making the decision, he was pleased to announce that the Pitman Prize winner for 2021 is Elizabeth Korevaar, who presented “Evaluation of statistical methods used to meta-analyse results from interrupted time series studies: a simulation study”.
Congratulations, Lizzie! |
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Statistical Computing and Graphics Section – Are you in?
The SSA has been approached about the creation of Statistical Computing and Graphics Section. Are you interested? This is your chance to join the Statistical Computing and Graphics Section Committee and help shape this new section. We are currently seeking expressions of interest from members wanting to get involved. Please fill in this EOI form if this is you. |
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You are invited: SSA and ASPAI AGMs - 17 August 2021
The 2021 Annual General Meetings of the Statistical Society of Australia, Incorporated and the Australian Statistical Publishing Association Inc will be held on Tuesday, 17 August 2021 from 5:30 pm to 6:15 pm via Zoom.
The SSA and ASPAI AGMs are available to members of SSA only. Please use registration link below if you would like to attend. You do not need to register separately for the talk following the AGMs.
This year’s AGMs will be followed by a presentation from Pitman Prize awardee Professor Rob J. Hyndman, Head of the Department of Econometrics & Business Statistics, Monash University.
Rob's talk is titled: " Uncertain Futures: What Can We Forecast and When Should We Give Up?". |
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Two SSA Members part of STA's Governance Structures SSA is a proud member of Science & Technology Australia (STA). We are particularly delighted that SSA now has two members with roles in STA’s governance structures. SSA Vice-President Professor Adrian Barnett was recently reappointed for a second term to STA’s Policy Committee, and our current Vice-President (Membership), Dr Susanna Cramb will be joining STA’s Equity, Diversity, and Inclusion Committee. Congratulations! |
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Top 10 Ideas in Statistics That Have Powered the AI Revolution
In an article published on 6 July 2021 in the “Columbia News”, Kim Martineau, Director of Science and Technology Communications at Columbia University, New York, presents the top 10 ideas in statistics that have powered the AI revolution. She refers to a recent paper by Andrew Gelman, a statistics professor at Columbia, and Aki Vehtari, a computer science professor at Finland’s Aalto University, who published a list in the Journal of the American Statistical Association of the most important statistical ideas produced in the last 50 years. |
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Can artificial intelligence answer important medical questions?
A collaboration between a biostatistician and a data scientist. |
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$2,000 scholarships available for two successful applicants!
The Australian Pharmaceutical Biostatistics Group (APBG) is providing a fantastic opportunity for undergraduates or new graduates in the data science and statistical fields to work together on this important conundrum.
Biostatisticians and data scientists often have different approaches to answering important clinical questions. Classical statistical regression methods used for prediction modelling are well understood in the statistical sciences and the scientific community that employs them. These methods tend to be transparent and are usually hypothesis driven but can overlook complex associations with limited flexibility when a high number of variables are investigated. In addition, when using classic regression modelling, choosing the ‘right’ model is not straightforward. Non-traditional machine learning algorithms, and machine learning approaches, may overcome some of the limitations of classical regression models in this new era of big data, but are not a complete solution as they must be considered in the context of the limitations of data used in the analysis.
In this project, you will receive a large dataset with an underlying correlation structure. You will work together with your assigned collaborator to discover the algorithm that best fits the data.
You will be expected to meet with the APBG steering committee to present updates on your project, provide a written report, code, and present your findings at our annual meeting which is to be held in December 2021.
Applications are welcomed from undergraduates or graduates of Data Science or Statistics or related fields who are based in Australia or New Zealand.
Apply before 15 August 2021. |
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Our Accreditation Committee needs you!
We are seeking expressions of interest from AStat accredited members wanting to join the Accreditation Committee. Get involved and help other members attain accreditation! Keep in mind that you would not be accredited yourself if it were not for the dedicated volunteers on SSA’s Accreditation Committee.
Committee tenure is usually for three years, but some committee members enjoy their time on the AC so much that they extend to six years! Meetings are held via Zoom every six weeks or so; sometimes just every other month. Accreditation applications are uploaded to Dropbox and the committee members are asked to read them prior to the meetings and then give their view on whether candidates meet SSA’s criteria for accreditation or not. In 2020 we received a total of 33 applications, many of them applications for reaccreditation which are usually very straightforward.
If you are interested, please contact me. If you would like to chat with someone on the committee before making a decision, please let me know and I will put you in touch with a committee member or the Chair.
I look forward to hearing from you.
Marie-Louise Rankin
SSA Executive Officer
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Workshop: Statistical Shape Analysis via Topological Data Analysis
The Statistical Society of Australia and the Early Career and Student Statistician Conference are offering their 2nd short course leading up to the conference, to be held on
25 Jul 2021, 11:00 AM - 3:00 PM AEST via Zoom.
About the short course:
As modern data applications become complex in size and structure, identifying the underlying shape and structure has become of fundamental importance. The classical approaches such as dimension reduction are challenging for handling these applications. Topological data analysis (TDA) is a rapidly developing collection of methods that focuses on the “shape” of data. TDA can uncover the underlying low-dimensional geometric and topological structures from high-dimensional datasets. TDA has been successfully applied to various areas, including biology, network data, material science, and geology, in recent years. The goal of the lecture is to introduce novel TDA methods that can capture geometric or topological information of data and make statistical inferences. This lecture aims to familiarize these new methods along with their applications to various types of data.
About the presenter:
Chul Moon received his Ph.D. in Statistics from the University of Georgia. He joined the Department of Statistical Science at Southern Methodist University as an Assistant Professor in 2018. His research interests include topological data analysis, empirical likelihood, and ranked set sampling. His research aims to develop statistical methods in biosciences and geosciences.
Prerequisites:
Basic statistical knowledge and R.
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Convex Optimization for Statistical and Machine Learning with CVXR
The Statistical Society of Australia and he Early Career Student Statistician Conference 2021 are offering this workshop on Convex Optimization for Statistical and Machine Learning with CVXR to be held on 24 July 2021, 11am -3:00pm AEST via Zoom.
Optimization plays an important role in fitting many statistical models. Some examples include least squares, ridge and lasso regression, Huber regression, and support vector machines. CVXR is an R package that provides an object-oriented modeling language for convex optimization. It allows the user to formulate convex optimization problems in a natural mathematical syntax rather than the standard form required by most solvers. Moreover, problems can be easily modified and re-solved, making the package ideal for prototyping new statistical methods. First, the user specifies an objective and set of constraints by combining constants, variables, and parameters using a library of functions with known mathematical properties. CVXR then applies disciplined convex programming (DCP) to verify the problem’s convexity. Once verified, the problem is automatically converted into quadratic or conic form and passed to a solver like OSQP, MOSEK, or GUROBI. We demonstrate CVXR’s modeling framework with several applications in statistics and machine learning.
About the presenter: Anqi Fu is a Ph.D candidate in the Electrical Engineering department at Stanford University. Her research focuses on developing algorithms and software for large-scale optimization with applications to data science. One of her recent projects leverages methods from optimal control to design treatment plans for cancer radiation therapy. Prior to starting her Ph.D, Anqi worked as a machine learning scientist at H2O.ai. She received an M.S. in Statistics from Stanford University, and a B.S. in Electrical Engineering and a B.A. in Economics from the University of Maryland, College Park.
Prerequisites: A working knowledge of statistics and linear algebra, and basic experience with a scripting language like R. We also invite attendees to bring problems of interest, which we will do our best to formulate and solve in CVXR.
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Science & Technology Australia's Reconciliation Action Plan
Members of SSA are invited to join Science & Technology Australia (STA) tomorrow for a virtual launch of STA's first Reconciliation Action Plan: 9 July 2021, 12pm AEST via Zoom
Across an awe-inspiring timespan of more than 65,000 years, Aboriginal and Torres Strait Islander peoples have created knowledge as Australia’s first scientists, technologists, engineers, and mathematicians. The songlines of this country are intricate scientific knowledge systems.
As the peak body for the science and technology sector, STA honours this long tradition. Their vision is for a reconciled and united Australia. A nation which faces the truth of our past with honesty and courage. A nation which sees the inspiring first cultures of this land as a great source of pride for all Australians.
After registering, you will receive a confirmation email containing information about joining the event. Please use the link below.
We look forward to seeing you there.
Misha Schubert
CEO, Science & Technology Australia
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Teaching Statistics – Special Issue: Teaching Data Science and Statistics: foundation and introductory
Teaching Statistics announces publication of a special issue “Teaching Data Science and Statistics: foundation and introductory”, edited by the journal’s editor-in-chief Helen MacGillivray along with Rob Gould and Jim Ridgway.
The various impacts on teaching of developments in data science, statistics, and their confluence are seen not only in the increasing inclusion of technology in teaching statistics but also in the broadening of data, contexts, statistical issues, and discussions at different educational levels, and across disciplines. This special issue is intended to provide impetus in furthering this progress and to celebrate the new subtitle of the journal, in the increasing awareness of how statistics and data science must work together in tackling real and complex datasets and problems involving complex data. The editorial continues some aspects of this discussion.
The overall aim of the special issue is to be useful to all who are actively involved in data education, particularly across disciplines. The special issue has been more than a year in the making, with both invited and contributed papers, and all refereed by reviewers of international standing and experience. As always, the emphasis is on scholarly writing and good practice in teaching, and many papers refer to, and build on, previous excellent work and literature and include valuable bibliographies. |
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Retracted study misused statistics and adverse event reports to claim that COVID-19 vaccines don’t offer “clear benefit” and caused deaths
“Statistics is a complex and delicate field requiring both high level training and experience. An aptitude for figures, or the ability to turn on a computer, just isn’t enough. Statistics is a job for professionals!” These are not my own words, but they are taken from the SSA brochure: “Statistics: a job for professionals.”
An article published this week on the website “Health Feedback” tells the story of how a flawed study arrived at the conclusion that COVID-19 vaccines don’t offer a “clear benefit” and caused deaths. A study conducted by Harald Walach, Rainer Klement and Wouter Aukema and published in the journal Vaccines in late June 2021, claimed that “For three deaths prevented by vaccination we have to accept two inflicted by vaccination.” The study was widely shared on social media sites before being retracted on 2 July.
The flawed methodology used by the researchers resulted in the resignation of two scientists on the editorial board who called the publication of the study “grossly negligent”. |
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Joint SSA Canberra Branch + Canberra Data Scientists Meeting
From supervised machine learning to causal heterogeneity modelling for personalised decision making
27 Jul 2021, 6:00 PM - 7:30 PM AEST via Zoom
The SSA Canberra Branch invites you to its June branch meeting, which will be held jointly with Canberra Data Scientists, and presented Prof. Jiuyong Li, University of South Australia.
About the talk:
Causal heterogeneity modelling emerges as an effective approach for personalised decision making and is used in personalised marketing and personalised medicine. In this talk, We will differentiate causal heterogeneity modelling from supervised machine learning and show some research and applications we have done in using causal heterogeneity modelling for decision making. We will give some common practice recommendations for using causal heterogeneity modelling methods. |
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We'd like to thank our other generous sponsors: |
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Now that ANZSC2021 is finished, let’s keep the great feeling going! Don’t forget to register for ECSSC, which is coming up really quickly. Come and support our young and budding statisticians and continue to network.
will be held from 26 July to 1 Aug 2021. There are many things to look forward to, such as an amazing line-up of keynote speakers from all occupations.
Not sure yet? It pays to register soon, because the first 120 paid registrations will receive a Menulog voucher worth A$25, generously sponsored by ACEMS, to be used during the conference. Enjoy your favourite take-away and socialise with your colleagues during one of our many social events!
And don’t forget: every delegate will receive a virtual goodie-bag! Register here.
See you at ECSSC2021!
ECSSC2021 Conference Committee
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A Song of Wind & Fire: a statistical journey through an uncertain world
Dr Rachael Quill
Wednesday 14 July, 12pm-1pm AEST via Zoom
In this lecture, Dr Rachael Quill will explore how shedding light on the uncertainties of wind flow across the environment can support informed decision-making in bushfire management and renewable energy generation.
Extreme fire behaviours are being witnessed at an increasing rate across Australia and the world. Such behaviours were recorded in 2003 as fires rushed from the mountains into the suburbs of Canberra, destroying 500 homes and sadly claiming 4 lives. Nearly two decades of scientific research since then has pushed the boundaries of our understanding in fire dynamics, bushfire prediction and emergency management. In this lecture, we will explore how improving the understanding of uncertainties around fire behaviour enables more informed fire management through seeing a fuller picture of an event.
The principles of accounting for uncertainty translate into many different fields. In the second half of this lecture, we will explore this notion in relation to renewable energy. Integrating renewable and intermittent power into national electricity grids is a global challenge in the pursuit of lowering our carbon emissions. Enabling accurate and timely prediction of resources, such as wind, involves understanding its inherent variability then communicating and accounting for uncertainty in prediction. In a world where hard decisions must be made to address global challenges, we need to ensure those decisions are made knowing the fullest picture possible. |
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If you have news from the Australian statistical community to share in Stats Matters and Events, please get in touch with us! We love getting feedback too.
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Statistical Society of Australia | PO Box 213 Belconnen ACT 2616 Australia 02 6251 3647 | www.statsoc.org.au |
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