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• CPD 181- Machine Learning II

  • Start
    23 Sep 2024
  • End
    11 Nov 2024
  • Location
    Online- 1 hour a week
  • Spaces left
    2

  Registration is closed

  The Social Research Centre and the Statistical Society of Australia (SSA) are very proud to offer statistical training from 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.

  Places are limited, please register early to take advantage of early bird discounts and secure a place.
  

  Short Course Description

  Social scientists and survey researchers are confronted with an increasing number of new data sources such as apps and sensors that often result in (para)data structures that are difficult to handle with traditional modeling methods. At the same time, advances in the field of machine learning (ML) have created an array of flexible methods and tools that can be used to tackle a variety of modeling problems. Against this background, this course discusses advanced ML concepts such as cross validation, class imbalance, Boosting and Stacking as well as key approaches for facilitating model tuning and performing feature selection. In this course we also introduce additional machine learning methods including Support Vector Machines, Extra-Trees and LASSO among others. The course aims to illustrate these concepts, methods and approaches from a social science perspective. Furthermore, the course covers techniques for extracting patterns from unstructured data as well as interpreting and presenting results from machine learning algorithms. Code examples will be provided using the statistical programming language R.

  Timeframe:

  September 24 – November 11, 2024. Weekly meetings at the following times:

  ▪ Week 1: Tuesday, September 24, 8:00-9:00 am AEST

  ▪ Week 2: Tuesday, October 1, 5:00-6:00 pm AEST

  ▪ Week 3: Tuesday, October 8, 5:00-6:00 pm AEDT

  ▪ Week 4: Tuesday, October 15, 5:00-6:00 pm AEDT

  ▪ Week 5: Tuesday October 22, 10:00-11:00 am AEDT

  ▪ Week 6: Tuesday October 29, 10:00-11:00 am AEDT

  ▪ Week 7: Tuesday, November 5, 10:00-11:00 am AEDT

  ▪ Week 8: Tuesday, November 12, 8:00-9:00 am AEDT
  

  Course Objectives

  By the end of the course, students will… ▪  have a profound understanding of advanced (ensemble) prediction methods ▪ have built up a comprehensive ML toolkit to tackle various learning problems ▪ know how to(critically) evaluate and interpret results from ''black-box'' models

  Topics

  1. Intro: Bias-variance trade-off, cross-validation (stratified splits, temporal cv) and model tuning (grid and random search)

  2. Classification: Performance metrics (ROC, PR curves, precision at K) and class imbalance (over- and undersampling, SMOTE)

  3. Ensemble methods I: Bagging and Extra-Trees

  4. Ensemble methods II: Boosting (Adaboost, GBM, XGBoost) and Stacking

  5. Variable selection: Lasso, elastic net and fuzzy/ recursive random forests

  6. Support Vector Machines

  7. Advanced unsupervised learning: Hierarchical clustering and LDA

  8. Interpreting (Variable Importance, PDP, ...) and reporting ML results

  Your instructor: Prof. Christoph Kern

  Christoph Kern is Junior Professor of Social Data Science and Statistical Learning at the Ludwig-Maximilians-University of Munich and Project Director at the Mannheim Centre for European Social Research (MZES). He received his PhD in social science (Dr. rer. pol.) from the University of Duisburg-Essen in 2016. Before joining LMU Munich, he was a Post-Doctoral Researcher at the Professorship for Statistics and Methodology at the University of Mannheim and Research Assistant Professor at the Joint Program in Survey Methodology (JPSM) at the University of Maryland. His work focuses on the reliable use of machine learning methods and new data sources in social science, survey research, and algorithmic fairness.

   Your instructor: Prof. Trent Buskirk

  Current positions: ▪ Professor and Provost Data Science Fellow at Old Dominion University ▪ Novak Family Professor of Data Science, Chair and Director at Bowling Green State University ▪ Adjunct Research Professor at the University of Michigan

  Dr. Buskirk is a Fellow of the American Statistical Association. His research includes the areas of Mobile and Smartphone Survey Designs, methods for calibrating and weighting nonprobability samples, and the use of big data and machine learning methods for health, social and survey science design and analysis. His research has been published in leading journals such as Cancer, Social Science Computer Review, Journal of Official Statistics, and the Journal of Survey Statistics and Methodology.
  

  Prerequisites

  Topics covered in Introduction to Machine Learning and Big Data (ML I), i.e.:

  ▪ Conceptual basics of machine learning (training vs. test data, model evaluation basics)

  ▪ Decision trees with CART

  ▪ Randomforests Familiarity with the statistical programming language R is strongly recommended.

  Participants are encouraged to work through one or more R tutorials prior to the first-class meeting. Some resources can be found here:

  ▪ https ://rstudio.cloud/learn/primers

  ▪ http ://www.statmethods.net/

  ▪ https ://swirlstats.com/

  ▪ https ://www.rcommander.com

  Grading will be based on:

  ▪ 4 homeworkassignments (10% each)

  ▪ 8 onlinequizzes (5% each) 

  ▪ Participation in discussion during the weekly online meetings (20% of grade)

  Early Bird Deadline
  Please book before 5 July 2024 to take advantage of the Early Bird Deadline.

  Disclaimer
  
  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 events@statsoc.org.au with the names, email addresses, and telephone numbers  of the participants in the group.
  
  Cancellation Policy
  Occasionally courses have to be cancelled due to a lack of subscription. Early registration ensures that this will not happen.
  
  Cancellations received prior to two weeks before the event will be refunded, minus the  Stripe processing fee (1.75% + $0.30 per transaction) and an SSA administration fee of $20. 

  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 events@statsoc.org.au.
  
  For any questions, please email events@statsoc.org.au

  Show details
• CPD-184 Introduction to Large Language Models for Statisticians

  • When
    15 Oct 2024
  •  
    1:30 PM - 5:00 PM
  • Location
    Online
  • Spaces left
    0

  Registration is closed

  The Early Career and Student Statisticians Network is warmly invites you to an introductory workshop on Large Language Models for Statisticians presented by Dr Emi Tanaka. 

  About the workshop:

  This workshop serves as an introduction to Large Language Models (LLMs), specifically tailored for statisticians. The concept behind LLMs are distilled and presented in a way that is accessible and relevant to those with a background in statistics. The workshop will help participants understand how LLMs can be integrated into existing workflows. Practical applications will be demonstrated primarily through the R programming language. Participants will receive all R codes used in the demonstration, enabling them to replicate the analyses and continue exploring LLMs on their own.

  Learning objectives:

  • Understanding the fundamental concepts of large Language models (LLMs)  and Generative Artificial Intelligence (genAI).
  • Exploring the role LLMs in modern data analysis and decision-making.
  • Gain insight into practical applications of LLMs in various domains.

  
  

  About the presenter:

  Dr Emi Tanaka is an Applied Statistician and Deputy Director at the Biological Data Science Institute at the Australian National University. Her primary interest is developing impactful methods and tools practitioners can readily use. She delivers numerous statistical workshops including data visualisation, data wrangling, reproducible practices, statistical modelling and statistical consulting. She was the inaugural recipient of the SSA Distinguished Presenter's Award based on the delivery of her workshops.

  Target audience:

  The workshop is suitable for statisticians, data analysts and professionals with a background in statistics who are interested in exploring the applications and implications of Large Language Models.

  
  

  Requirements:

  • Computer
  • Stable internet connection.
  • Install the video conferencing software, zoom and know how to use it.
  • Basic statistics (e.g. simple linear regression, hypothesis testing, basic summary statistics and plots)

  Please note that some participants may have difficulty installing the software ollama (particularly Window users). Detailed instructions for installing the necessary software including ollama, will be provided.  However, technical assistance for software installation is beyond the scope of the workshop, so participants will need to manage the installation on their own.  

  Desirable:

  • Microphone and web camera.
  • Some familiarity with R.
  • Admin rights to their computer to install software like ollama (https://ollama.com/) and R package.
  • Basic understanding of machine learning concepts.

  Timetable:

  1:30-3:00pm session 1

  3:00-3:30 Break

  3:30-5:00pm Session 2

  All profits from this workshop will be given as a sponsorship to the SSA to support early career statisticians.

  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 two weeks before the event will be refunded, minus the  Stripe processing fee (1.75% + $0.30 per transaction) and an SSA administration fee of $20. 

  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 events@statsoc.org.au.
  
  For any questions, please email events@statsoc.org.au

  Show details
• Moyal Medal Presentation and Lecture

  • When
    17 Oct 2024
  •  
    6:00 PM - 7:30 PM
  • Location
    G25 Lecture Theatre, Michael Kirby Building, 17 Wally’s Walk, Macquarie University

  The Moyal Medal Committee and Macquarie University Faculty of Science and Engineering are pleased to invite you to the Moyal Medal Presentation and Lecture to celebrate the achievements of this year's Medalist, Professor Alan Welsh of The Australian National University.
   
  The Moyal Medal, awarded annually, honours distinguished research contributions in mathematics, physics, or statistics, in tribute to the late Professor José Enrique Moyal who was one of Australia’s most remarkable scientists. His insight into the interaction between mathematics, physics and statistics led him to make contributions to these disciplines which have had far-reaching ramifications in all three fields.
  
  The 2024 Medalist, Professor Welsh, is the EJ Hannan Professor of Statistics at the Australian National University (ANU). Professor Sakkie Pretorius, Deputy Vice Chancellor of Research at Macquarie University, will present the 2024 Moyal Medal to Professor Alan Welsh. 
   
  The artificial intelligence (AI) tools that are all around us rely on statistical methods to make sense of vast quantities of data. Professor Welsh’s lecture, titled "Up and Down: The Challenge of Double Descent," will explore the intriguing phenomenon of 'double descent' in AI and big data. Using visuals, he will explain how this surprising behaviour, tied to model complexity, data distribution, and training dynamics, reshapes our understanding of statistical models and challenges traditional methods.
  
  Learn more about Professor Alan Welsh and the evening’s topic, and the Moyal Medal.
  
  This year we are also having a poster presentation that demonstrates the exciting work that students and staff in our Faculty are doing in statistics, astronomy, mathematics, physics, and computer science. This will be running in the venue foyer 5:00pm-6:00pm so please join us if you can.
   
  If you have any questions about this event, please contact us at fse.outreach@mq.edu.au.

   

  Please register for seating purposes.

  Moyal Medal Registration link

   
  

  
  

  Show details
• Women in STEM Careers and Entrepreneurship Masterclass

  • Start
    21 Oct 2024
  • End
    23 Oct 2024
  • Location
    Level 9, Paramatta City Campus, Western Sydney University.

  Join the Women in STEM Careers and

  Entrepreneurship Masterclass this October!

  Unlock your potential at the upcoming Women in STEM Careers and Entrepreneurship Masterclass, hosted by the Australian Mathematical Sciences Institute and Western Sydney University. This exclusive event will take place from 21 - 23 October at the Parramatta City Campus, Western Sydney University.

  Designed for women STEM researchers, this masterclass offers a unique opportunity to delve into Australia’s research commercialisation and innovation ecosystem. Gain insights directly from industry and university experts in research innovation, and hear success stories from researchers who have transitioned into leading roles in startups or R&D teams.

  Who should attend?

  If you are a STEM research student or an early to mid-career researcher, this masterclass is tailored for you. We especially encourage those who have participated in an APR Internship, funded by APR’s WISE program, to take advantage of available sponsorships covering accommodation and travel expenses.

  Event Details

  • Time and Date: 9am - 5pm AEDT, 21 - 23 October 2024.
  • Location: Level 9, Paramatta City Campus, Western Sydney University.
  • Cost: $130 GA, Free for APR.Intern WiSE subsidy recipients.

  Join us at the forefront of STEM innovation and entrepreneurship.

  We look forward to welcoming you to Sydney this October!

  For more information and to register click here.

  Show details
• SSA Vic & Tas October 2024 Event - SSA and MLAI Present: Industry Showcase

  • When
    22 Oct 2024
  •  
    6:00 PM - 7:30 PM
  • Location
    Level 1, 115 Dover Street Cremorne

  Register

  SSA and MLAI Present: Industry Showcase
  

  
  

  Time: 6pm to 7:30, 2024-10-22

  
  

  Place: Level 1, 115 Dover Street Cremorne

  
  Speakers:
  

  1. Teagan Buckley: Data Specialist, Media Monks,
     TBD
     
  2. Lizzie Silver:  Senior Data Scientist, WSP Digital
     TBD
     
  3. Nick Read: Data Science Leader, FloodMapp
     Abstract: FloodMapp delivers street-level flood intelligence: a live mapping feed that shows flood inundation before, during and after an event. I'll talk about some of the software we've built that consumes river-gauge and meteorology data to produce hourly forecast flood extents.
  4. Patrick Robotham: Chief Scientist, Prophet
     Abstract: Prophet estimates the return on investment for various forms of advertising using geographical time series data. I’ll discuss some statistical challenges and lessons learned from modelling

  Show details
• ECSSN and NZSA October Webinar-Presenting effectively at mixed-mode events presented by Karen Lamb

  • When
    28 Oct 2024
  •  
    3:00 PM - 4:00 PM
  • Location
    Online

  Register

  ECSSN and NZSA are proud to present -Presenting effectively at mixed-mode events presented by Karen Lamb

  Conferences and meetings are now commonly held in mixed-mode formats with both in-person and virtual presentations and audience members. This makes things challenging for presenters. In this presentation, Karen will offer tips on delivering effective presentations in these mixed-mode settings.

  Bio:

  
  

  A/Prof Karen Lamb is co-Head of the Biostatistics Node in the Methods and Implementation Science for Clinical and Health research (MISCH) Hub at the University of Melbourne. She has worked as a statistician for more than 15 years and has delivered over 50 conference presentations, both in person and online. She is an active member of the SSA and created the SSA mentoring program which launched in 2020.

  
  

  Show details
• SSA NSW October Meeting - Christopher K Wikle - 2024 Data Science and Statistics (DSS) Lecture, from School of Mathematics and Applied Statistics, University of Wollongong (UOW)

  • When
    30 Oct 2024
  •  
    11:30 AM - 12:30 PM
  • Location
    Building 43 Room G01, University of Wollongong

  The SSA NSW branch is thrilled to collaborate with UOW School of Mathematics and Applied Statistics on their annual Data Science and Statistics (DSS) Lecture. This year's lecturer is Christopher K Wikle, Distinguished Professor in the Department of Statistics at the University of Missouri, USA.

  Date: Wednesday 30 October 2024
  

  Time: 11.30am - 12.30pm: in-person-only lecture, with light refreshments to follow

  Venue: Building 43 Room G01, University of Wollongong, parking available on campus for carpool. Sign up here to carpool. 

  RSVP: Register here.

  Speaker: Christopher K Wikle

  
  

  Title:  The Ship Has Sailed: Where Should We Steer It? (Climate Adaptation Needs Uncertainty Quantification)

  
  

  Abstract:

  Earth’s climate is changing due to anthropogenic influences. Although there are still well-meaning attempts to mitigate the drivers of this change (e.g., reduction of greenhouse gas emissions), it is widely believed that such changes will be “too little, too late.” Thus, for many, the focus has shifted to “climate change adaptation” in which decision makers modify their response to or anticipation of the numerous risks associated with climate change. There are many different approaches that can be taken when one adapts to climate change, ranging from resistance to retreat. The decision on the most appropriate way forward (how to steer the ship) requires a coherent, cohesive, and collective response across localities, sectors of society, and scales of governance. Such decisions require information from many different sources (e.g., from climate models, from impact assessments, from political and social scientists, …), and these sources come with uncertainty. In addition, this process is inherently multi-disciplinary and requires teams of scientists and decision makers working together. Although it is well known that informed decisions must account for uncertainty, quantification of that uncertainty across multiple disciplines, information sources, and complex decision pathways is in its infancy. This relatively non-technical talk will describe some of the challenges and will argue that statistical science offers a path forward through multi-level (deep) modelling. Such approaches will likely borrow from Bayesian statistics as well as utilise modern surrogate modelling techniques and hybrid “AI”-statistical methods. Several examples will be presented to illustrate these points. 

  Biography:

  Christopher K. Wikle is Curators’ Distinguished Professor and Chair of Statistics at the University of Missouri (MU), with additional appointments in Soil, Environmental and Atmospheric Sciences and the Truman School of Public Affairs. He received a PhD co-major in Statistics and Atmospheric Science in 1996 from Iowa State University. He was research fellow at the National Center for Atmospheric Research from 1996-1998, after which he joined the MU Department of Statistics.

  His research interests are in spatial and spatio-temporal statistics applied to environmental, ecological, geophysical, agricultural and federal survey applications, with particular interest in dynamics. His work has been concerned with formulating computationally efficient deep hierarchical Bayesian models motivated by scientific principles, with more recent work at the interface of deep neural models in machine learning.

  Awards include elected Fellow of the American Statistical Association (ASA), Institute of Mathematical Statistics (IMS), elected Fellow of the International Statistical Institute (ISI), Distinguished Alumni Award from the College of Liberal Arts and Sciences at Iowa State University, ASA Environmental (ENVR) Section Distinguished Achievement Award, co-awardee 2017 ASA Statistical Partnership Among Academe, Industry, and Government (SPAIG) Award, the MU Chancellor’s Award for Outstanding Research and Creative Activity in the Physical and Mathematical Sciences, the Outstanding Graduate Faculty Award, and Outstanding Undergraduate Research Mentor Award. His book Statistics for Spatio-Temporal Data (co-authored with Noel Cressie) was the 2011 PROSE Award winner for excellence in the Mathematics Category by the Association of American Publishers and the 2013 DeGroot Prize winner from the International Society for Bayesian Analysis. His latest book, Spatio-Temporal Statistics with R, with Andrew Zammit-Mangion and Noel Cressie, was published in 2019 and won the 2019 Taylor and Francis award for Outstanding Reference/Monograph in the Science and Medicine category. Dr. Wikle is Associate Editor for several journals and is one of six inaugural members of the Statistics Board of Reviewing Editors for Science.

   

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• CPD 185– Statistical Communication Workshop

  • Start
    6 Nov 2024
  • End
    13 Nov 2024
  • Location
    Online- 1.5 hours a week
  • Spaces left
    12

  Register

  NSW Branch presents Statistical Communication Workshop by Dr Nicole Mealing.

  Do you struggle to explain to your audience why your statistical results matter? Or does your audience have difficulty understanding the data insights you communicate? Come along to this workshop to enhance your statistical communication skills.

  This workshop will focus on what to consider before you start shaping communication outputs and how to deliver your data derived messages effectively. We’ll use worksheets to help you communicate statistical insights that derive understanding or action from your audiences.

  These training sessions will enable participants to:

  • Understand the importance of context and audience
  • Select appropriate visual aids to successfully communicate data insights
  • Identify opportunities to simplify your message and direct the audience to the most important parts of your data narrative

  Sessions

  1. Wednesday 6 November: 11:00 am – 12:30 pm AEDT

  2. Wednesday 13 November: 11:00 am – 12:30 pm AEDT

  Instructor:

  Dr Nicole Mealing is a Statistical Consultant, Statistical Communicator and Data Coach at Simplify Stats. She has a PhD in biostatistics and over 15 years of experience working for the public sector, academia and private institutions. She has taught statistics at many universities in Sydney, and now teaches her own specially designed workshops through Simplify Stats.

  
  

  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 two weeks before the event will be refunded, minus the  Stripe processing fee (1.75% + $0.30 per transaction) and an SSA administration fee of $20. 

  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 events@statsoc.org.au.
  
  For any questions, please email events@statsoc.org.au

  
  

  Show details
• SSA NSW Branch 2024 Annual Event with JB Douglas Award and Annual Lecture by Prof. Matt Wand

  • When
    14 Nov 2024
  •  
    2:00 PM - 10:00 PM
  • Location
    Sutherland Room, The University of Sydney

  Register

  Please join us for the NSW SSA branch annual event on Thursday 14th November at the Sutherland Room, The University of Sydney from 2pm. The afternoon will start with presentations from PhD students from around NSW for the J. B. Douglas Awards. We are then proud to present our Annual Lecture by Distinguished Professor Matt Wand at 6pm, followed by the Annual dinner from 7pm.

  We hope to see everyone there.

  Program overview
  

  2.00pm – 6:00pm – J. B. Douglas Award presentations (with refreshment break)

  6.00pm – 7.00pm – Annual lecture by Professor Matt Wand

  7.00pm – Annual dinner, please register here

  
  

  The location

  The Sutherland Room is located at the University of Sydney's Camperdown campus.

  J. B. Douglas nominees

  TBA

  Annual lecture
  

  Speaker: Professor Matt Wand

  Matt P. Wand is a Distinguished Professor of Statistics at the University of Technology Sydney. He has held faculty appointments at Harvard University, Rice University, Texas A&M University, the University of New South Wales and the University of Wollongong. Professor Wand is an elected fellow of the Australian Academy of Science, the American Statistical Association and the Institute of Mathematical Statistics. He was awarded two of the Australian Academy of Science's medals for statistical research: the Moran Medal in 1997 and the Hannan Medal in 2013. In 2014 he was awarded the Statistical Society of Australia's Pitman Medal. He has co-authored 3 books, more than 130 statistics journal articles and 10 R packages.
  

  Title: Machine Learning Meets Likelihood Theory

  Abstract:

  Machine learning is a cousin of statistics that is concerned with the development of algorithms for learning from data. Examples of machine learning algorithms are artificial neural networks, reinforcement learning and expectation propagation. However, theory concerning statistical properties is scant. This lecture will provide a non-technical overview of the speaker's involvement in the evaluation of particular machine learning paradigms through the classical statistics prism of likelihood theory. For example, if expectation propagation is used for approximate fitting of a frequentist logistic mixed model then are the estimators of the model parameters asymptotically normal with Cramer-Rao lower bound variances? The lecture will also touch upon the following interesting side trip from this body of research: the derivation of new asymptotic normality results for exact maximum likelihood. The body of research goes back to the late 2000s and has involved leading Australian theoretical statisticians Peter Hall and Iain Johnstone, as well as several other Australia-based and U.S.A.-based statisticians.

  Our Sponsors

  If your organisation can sponsor a small amount, we would appreciate this. All sponsor logos will be displayed in the J.B. Douglas programme.

  Please note that all our events are governed by the Code of Conduct. This means that we absolutely do not tolerate unacceptable behaviour, including any form of harassment. This applies to both members and non-members. If you have any concerns, please contact Gordana Popovic.

  Any questions, please feel free to contact the NSW Branch Secretary. 

  Show details
• NSW Branch: 2024 Annual Dinner

  • When
    14 Nov 2024
  •  
    7:00 PM - 10:00 PM
  • Location
    Sutherland Room, The University of Sydney
  • Spaces left
    39

  Register

  The 2024 NSW branch annual dinner will be held at the Sutherland Room, The University of Sydney, Thursday 14th November from 7PM, right after the Annual Lecture. The dinner will be in a buffet setting, please make sure to specify if you have any dietary requirement.

  To support our early career and student Statisticians community we are providing a discount:

  • If you are a student or transitional members, you will be able to use your corresponding registration type provided directly;
  • If you are not currently in the two membership type but within 5 years post your last Statistics degree, please send an email to secretary.nswbranch@statsoc.org.au with your name, last degree name, name of institution, time of your gradation, membership status and current position, we will verify and assist you with your registration. 

  
  

  The location

  The Sutherland Room is located at the University of Sydney's Camperdown campus.

  Our Sponsors

  If your organisation can sponsor a small amount, we would appreciate this. All sponsor logos will be displayed in the J.B. Douglas programme.

  
  

  Please note that all our events are governed by the Code of Conduct. This means that we absolutely do not tolerate unacceptable behaviour, including any form of harassment. This applies to both members and non-members. If you have any concerns, please contact Gordana Popovic. 

  Any questions, please feel free to contact the NSW Branch Secretary.

  Show details
• ECSSC 2024 Christchurch Hub Registration

  • Start
    18 Nov 2024
  •  
  • End
    21 Nov 2024
  •  
  • Location
    University of Canterbury, Christchurch NZ

  Register

  This registration page is sponsored by:

  
  

  The Early Career & Student Statisticians Conference (ECSSC) is a biennial conference held during the interstitial years of the Australian Statistical Conference (ASC).

  It is jointly organised by the ECSS Network of the Statistical Society of Australia (SSA), and the Student and Early Career Statisticians Network (SECS) of the New Zealand Statistical Association (NZSA).

  For 2024, we are excited to coordinate three local hubs: Perth, Hobart, and Christchurch; as well as offer a livestream.

  Aims

  The aims of this event are:

  Provide an opportunity to socialise and share ideas amongst peers.

  Build and expand professional networks for mutual support and collaboration.

  Discuss new techniques and technologies applicable to statistics and data science.

  Promote the role of statistics in academia, government, and industry.

  An “Early Career or Student Statistician” is anyone who is currently studying statistics or data science, or has graduated in the last five years and works with statistics. There is no age restriction.

  It will pay to join the SSA and enjoy all the benefits, like discount rates on this conference.

  Full-time student membership ($20)

  Discounted student membership of SSA is available to those who are engaged in full-time studies and do not have an income. If you earn a salary you will generally not qualify for student membership. If you are unsure of your status please feel free to contact SSA at eo@statsoc.org.au with information about your student status and employment status (full-time, part-time, casual or permanent, name of employer) and an individual assessment will be made.

  Please email evidence of your current full-time enrolment status to SSA’s membership officer to eo@statsoc.org.au after signing up. This can be either a copy of the student identity card issued by the educational institution or a document providing evidence signed and verified by the institution. If proof of full-time student status has not been received within 14 days of signing up with SSA, the membership application will be rejected and a refund issued, minus a $10 admin fee.

  Student members will receive the weekly SSA newsletter and have online access to four copies of the "Australian and New Zealand Journal of Statistics" and six electronic issues of "Significance" each year.

  Early Career Membership ($140)

  This discounted level of membership is available to members transitioning or having transitioned from full-time university studies to employment within the last three years. The fee is half the cost of full membership, with all the benefits of full membership.

  Format

  ECSSC2024 is a hybrid event held over four half-days across three in-person hubs. For the best experience, delegates are strongly encouraged to attend one of these hubs either in Perth, Hobart, or Christchurch. Nevertheless, presenters at each hub will be livestreamed to the other hubs and to the online audience.

  
  

  
  

  Cancellation Policy
  
  Cancellations received prior to two weeks before the event will be refunded, minus the  Stripe processing fee (1.75% + $0.30 per transaction) and an SSA administration fee of $20. 

  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 events@statsoc.org.au.
  
  For any questions, please email events@statsoc.org.au

  
  

  Show details
• Early Career & Student Statisticians Conference 2024

  • Start
    18 Nov 2024
  • End
    21 Nov 2024
  • Location
    Hobart, Perth, New Zealand

  Join us for the biennial Early Career & Student Statisticians Conference (ECSSC). Organised by the ECSS Network of SSA and SECS Network of NZSA, this event offers invaluable insights and networking opportunities.

  This year, we're excited to host local hubs in Perth, WA, Hobart, Tasmania and Christchurch, New Zealand, as well as a livestream option. Don't miss out on this incredible experience!

  To register for the Perth Hub click here.

  To register for the Hobart Hub click here.

  To register for the Christchurch Hub click here.

  If you intend on attending online, click any of the hubs to register.
  

  Important Dates:

  • 1 July 2024: Call for abstracts
  • 11 July 2024: Registrations open
  • 26 July 2024: Deadline for abstract submission

  Please note that these dates might be adjusted as the conference approaches. The conference website is  https://ecssc2024.netlify.app/
  
  

   This registration page is sponsored by:

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• ECSSC 2024 Hobart Hub Registration

  • Start
    18 Nov 2024
  •  
  • End
    21 Nov 2024
  •  
  • Location
    University of Tasmania, Hobart Tas

  Register

  This registration page is sponsored by:

  
  

  The Early Career & Student Statisticians Conference (ECSSC) is a biennial conference held during the interstitial years of the Australian Statistical Conference (ASC).

  It is jointly organised by the ECSS Network of the Statistical Society of Australia (SSA), and the Student and Early Career Statisticians Network (SECS) of the New Zealand Statistical Association (NZSA).

  For 2024, we are excited to coordinate three local hubs: Perth, Hobart, and Christchurch; as well as offer a livestream.

  Aims

  The aims of this event are:

  Provide an opportunity to socialise and share ideas amongst peers.

  Build and expand professional networks for mutual support and collaboration.

  Discuss new techniques and technologies applicable to statistics and data science.

  Promote the role of statistics in academia, government, and industry.

  An “Early Career or Student Statistician” is anyone who is currently studying statistics or data science, or has graduated in the last five years and works with statistics. There is no age restriction.

  It will pay to join the SSA and enjoy all the benefits, like discount rates on this conference.

  Full-time student membership ($20)

  Discounted student membership of SSA is available to those who are engaged in full-time studies and do not have an income. If you earn a salary you will generally not qualify for student membership. If you are unsure of your status please feel free to contact SSA at eo@statsoc.org.au with information about your student status and employment status (full-time, part-time, casual or permanent, name of employer) and an individual assessment will be made.

  Please email evidence of your current full-time enrollment status to SSA’s membership officer to eo@statsoc.org.au after signing up. This can be either a copy of the student identity card issued by the educational institution or a document providing evidence signed and verified by the institution. If proof of full-time student status has not been received within 14 days of signing up with SSA, the membership application will be rejected and a refund issued, minus a $10 admin fee.

  Student members will receive the weekly SSA newsletter and have online access to four copies of the "Australian and New Zealand Journal of Statistics" and six electronic issues of "Significance" each year.

  Early Career Membership ($140)

  This discounted level of membership is available to members transitioning or having transitioned from full-time university studies to employment within the last three years. The fee is half the cost of full membership, with all the benefits of full membership.

  Format

  ECSSC2024 is a hybrid event held over four half-days across three in-person hubs. For the best experience, delegates are strongly encouraged to attend one of these hubs either in Perth, Hobart, or Christchurch. Nevertheless, presenters at each hub will be livestreamed to the other hubs and to the online audience.

  
  

  
  

  Cancellation Policy
  
  Cancellations received prior to two weeks before the event will be refunded, minus the  Stripe processing fee (1.75% + $0.30 per transaction) and an SSA administration fee of $20. 

  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 events@statsoc.org.au.
  
  For any questions, please email events@statsoc.org.au

  
  

  Show details
• Expression of interest for financial assistance to attend ECSSC 2024

  • Start
    18 Nov 2024
  • End
    21 Nov 2024
  • Location
    Christchurch, Hobart, Perth or online

  Registration is closed

  Thank you for your interest in attending the Early Career and Student Statistician Conference.

  Even though early bird registration has ended, anyone applying now will receive $200 towards the registration fee.
  

  Eligibility criteria:

  • You are a student.
  • You do not have a company or university that can cover your registration fees.
  • Presentation is not required for eligibility.
  •  Have registered to attend the conference.( We will focus on in-person attendance but will also offer an option to attend online.)
  •  The scholarship will offset the early-bird registration fee $200
  •  Applicants will need to write briefly about how attending conference will  benefit them.
  • Recipients will be asked to write a blurb for newsletter
  • 
    

  If you have registered your interest, please register now for the conference and hold off on paying the invoice. We look forward to your participation!

  
  

  Show details
• ECSSC 2024 Perth Hub Registration

  • Start
    18 Nov 2024
  •  
  • End
    21 Nov 2024
  •  
  • Location
    Curtin University, Perth WA

  Register

  This registration page is sponsored by:
  

  The Early Career & Student Statisticians Conference (ECSSC) is a biennial conference held during the interstitial years of the Australian Statistical Conference (ASC).

  It is jointly organised by the ECSS Network of the Statistical Society of Australia (SSA), and the Student and Early Career Statisticians Network (SECS) of the New Zealand Statistical Association (NZSA).

  For 2024, we are excited to coordinate three local hubs: Perth, Hobart, and Christchurch; as well as offer a livestream.

  Aims

  The aims of this event are:

  Provide an opportunity to socialise and share ideas amongst peers.

  Build and expand professional networks for mutual support and collaboration.

  Discuss new techniques and technologies applicable to statistics and data science.

  Promote the role of statistics in academia, government, and industry.

  An “Early Career or Student Statistician” is anyone who is currently studying statistics or data science, or has graduated in the last five years and works with statistics. There is no age restriction.

  It will pay to join the SSA and enjoy all the benefits, like discount rates on this conference.

  Full-time student membership ($20)

  Discounted student membership of SSA is available to those who are engaged in full-time studies and do not have an income. If you earn a salary you will generally not qualify for student membership. If you are unsure of your status please feel free to contact SSA at eo@statsoc.org.au with information about your student status and employment status (full-time, part-time, casual or permanent, name of employer) and an individual assessment will be made.

  Please email evidence of your current full-time enrolment status to SSA’s membership officer to eo@statsoc.org.au after signing up. This can be either a copy of the student identity card issued by the educational institution or a document providing evidence signed and verified by the institution. If proof of full-time student status has not been received within 14 days of signing up with SSA, the membership application will be rejected and a refund issued, minus a $10 admin fee.

  Student members will receive the weekly SSA newsletter and have online access to four copies of the "Australian and New Zealand Journal of Statistics" and six electronic issues of "Significance" each year.

  Early Career Membership ($140)

  This discounted level of membership is available to members transitioning or having transitioned from full-time university studies to employment within the last three years. The fee is half the cost of full membership, with all the benefits of full membership.

  Format

  ECSSC2024 is a hybrid event held over four half-days across three in-person hubs. For the best experience, delegates are strongly encouraged to attend one of these hubs either in Perth, Hobart, or Christchurch. Nevertheless, presenters at each hub will be livestreamed to the other hubs and to the online audience.

  
  

  
  

  Cancellation Policy
  
  Cancellations received prior to two weeks before the event will be refunded, minus the  Stripe processing fee (1.75% + $0.30 per transaction) and an SSA administration fee of $20. 

  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 events@statsoc.org.au.
  
  For any questions, please email events@statsoc.org.au

  
  

  Show details
• 9th Biennial ACSPRI Social Science Methodology Conference

  • Start
    27 Nov 2024
  • End
    29 Nov 2024
  • Location
    Holme Building, University of Sydney

  ACSPRI is a consortium of universities, government research agencies and not-for profit research organisations, established as a non-profit organisation in 1976 to support and promote social science. They run intensive courses on both qualitative and quantitative research methods; develop Open source computer-assisted survey software; and undertake survey and infrastructure projects for researchers from member organisations.

  The ACSPRI conference is multi-disciplinary and brings together researchers and methodologists from a range of environments and contexts and contexts.

  CALL FOR PAPERS: 9th Biennial ACSPRI Social Science Methodology Conference 2024

  Conference dates: Wednesday November 27 – Friday November 29, 2024

  Venue: Holme Building, The University of Sydney, Sydney, Australia

  The call for papers is now open. We welcome proposals for presentations (abstract reviewed), short videos and posters. Submissions close on 20 September 2024.

  A unique feature of this conference is that it is multi-disciplinary and brings together researchers and methodologists from a range of environments and contexts.

  The conference is organised around four themes:

  1. Research paradigms and designs;
  2. Research methods and techniques;
  3. Research technology and tools;
  4. Datasets, data collections and data archiving.

  There will be three types of submissions considered:

  1. Presentations where an abstract is reviewed (abstract in the conference proceedings).
  2. Posters - including a student poster competition (abstract in the conference proceedings).
  3. Short videos (5 minutes) - including a student short video competition (abstract in the conference proceedings).

  More details will appear on the conference website soon

  Some important dates:

  • Late August 2024: Earlybird registration opens
  • 20 September 2024: Abstract submission closes
  • 11 October 2024: Earlybird registration closes
  • 13 November 2024: Final date for submission of short videos
  • 27 November 2024: Conference opens

  Show details
• The International Environmetrics Society (TIES) Conference 2024

  • Start
    2 Dec 2024
  •  
  • End
    5 Dec 2024
  •  
  • Location
    Adelaide

  The International Environmetrics Society (TIES) is a non-profit organization aimed to foster the development and use of statistical and other quantitative methods in the environmental sciences, environmental engineering and environmental monitoring and protection. To this end, the Society promotes the participation of statisticians, mathematicians, scientists and engineers in the solution of environmental problems and emphasizes the need for collaboration and for clear communication between individuals from different disciplines and between researchers and practitioners.

  All contributions related to environmetrics are welcome from across academia, research institutes, government, business and industry.

  For information on the conference click here.

  Key Dates:

  Deadline for Invited Paper Sessions	15th July 2024
  Deadline for Contributed Papers	15th Aug 2024
  Invited paper contributors informed of outcome	31st July 2024
  Contributed paper authors informed of outcome	9th Sept 2024
  Registration opens	15th July 2024
  Deadline for early registration	23rd Sept 2024

  
  

  For questions contact: John Boland john.boland@unisa.edu.au

  
  

  Show details
• International Statistics Conference ISC 2024

  • Start
    28 Dec 2024
  •  
  • End
    29 Dec 2024
  •  
  • Location
    Sri Lanka

  
  

  Show details
• Logistic Regression 5 Day Masterclass

  • Start
    24 Feb 2025
  • End
    28 Feb 2025
  • Location
    Deakin University’s Melbourne CBD campus 727 Collins Street, Docklands VIC 3008

  Deakin Epidemiology is pleased to offer a summer Masterclass focused on Logistic regression to be delivered by arguably the world’s most famous teacher of this statistical technique – Prof. Stanley Lemeshow. In years past, Lemeshow together with Ken Rothman offered back-to-back masterclasses in Biostats and Epi in Tasmania which were a bit of an institution, with many epidemiologists and biostatisticians building their knowledge and networks by heading south for a healthy dose of upskilling or as a refresher. Stan has agreed to offer this program onshore once again in Australia, this time at Deakin University’s Melbourne CBD campus 727 Collins Street, Docklands VIC 3008.

  This 5-day course (Feb 24-28, 2025) will provide theoretical and hands-on practical knowledge and skills in statistical modeling with an in-depth focus on logistic regression analysis – the standard method for regression analysis of binary, multinomial and ordinal response data in health research. Each day comprises a 4-hr class in the morning and a 2-hr practical session in the afternoon and opportunities to network with fellow health and medical practitioners and researchers.”

  Places are limited, so get in early! For more information click here!”

  
  

  Show details
• Spatial Statistics 2025: At the Dawn of AI

  • Start
    15 Jul 2025
  •  
  • End
    18 Jul 2025
  •  
  • Location
    NH Leeuwenhoorst, Noordwijk, The Netherlands

  During the Spatial Statistics 2025 conference in Noordwijk, the Netherlands, specific attention will be given to the opportunities, including challenges to be addressed, that Artificial Intelligence (AI) opens up and how spatial statistics can be developed further with AI.

  The latest developments in spatial statistics will be presented, emphasising their contributions at the dawn of AI, now and in the future. The optimal use of collected data, predicting in space and time, object recognition and segmentation, and transferability in the presence of spatial and temporal correlations are typical, but not exhaustive examples.

  For more information on the conference:

  https://www.elsevier.com/events/conferences/all/spatial-statistics

  
  

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• Biometrics in the Bush Capital 2025 - external event

  • Start
    24 Nov 2025
  • End
    28 Nov 2025
  • Location
    Canberra

  Come join the International Biometrics Society Australasian Region's biannual conference in the bush capital Canberra!

  https://biometricsociety.org.au/conference2025/

  Show details