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• CPD 187-Sampling II

  • Start
    22 May 2025
  •  
    11:00 AM
  • End
    12 Jun 2025
  • Location
    Online- Weekly 1 hour meetings taking place Thursdays
  • Spaces left
    15

  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.
  

   Topics:

  1. Multistage Sampling

  2. Multistage Sampling

  3. Multistage Sampling & Area Sampling

  4.    Multiphase Design

  Timeframe:

  May 22 – June 12, 2025. Weekly Meetings taking place Thursdays, 11:00 am – 12:00 pm AEST.

  Course Objectives
  By the end of the course, participants will… ▪ understand the principles of multistage sampling and its components ▪ be able to design and implement multistage sampling with different sampling techniques ▪ be familiar with area sampling and how to use it in various contexts ▪ understand multiphase design and be able to implement it in various survey context

  Your instructor: Raphael Nishimura, PhD 

  Raphael Nishimura is the Director of Sampling Operations in Survey Research Operations at the Survey Research Center (SRC) in the Institute of Social Research of the University of Michigan. He has been working with sampling and survey statistics for over ten years. He holds a PhD in survey methodology from the University of Michigan and a bachelor’s degree in statistics from the University of São Paulo. His main research interest includes sampling methods, survey nonresponse and adaptive/responsive designs. Nishimura is also the director of the Sampling Program for Survey Statisticians of the SRC Summer Institute for Survey Research Techniques
  

  Prerequisites

  Sampling I or equivalent knowledge. Some experience with the R statistical computing software is helpful.

   Grading will be based on:

  ▪ 4 Homework assignments (50% of grade)

  ▪ 4 Quizzes (one at the start of each online session; 15% of grade)

  ▪ Participation in discussion during the weekly online meetings, submission of questions in the weekly discussion forum, demonstrating understanding of the required readings and video lectures, and positive contributions on the Discussion Forum, see below (10% of grade)

  ▪ A final open-book online exam (25% of grade)

  Early Bird Deadline

  Please book before 31 March 2025 to take advantage of the Early Bird Deadline.

  Prices include GST. There is also a discount of $150 for Sampling 2 if registering at the same time as Sampling 1 or have completed Sampling 1 in the past.
  

  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
• SSA ACT Branch May Event: Hidden Statistical Thinking—Weaving Stories of Strength on Integrating Indigenous Perspectives Across the Curriculum

  • When
    27 May 2025
  •  
    5:45 PM
  • Location
    CBE Lecture Theatre 1, ANU College of Business & Economics, Building 26C, The Australian National University (ANU Building 26C), or via Zoom.

  SSA ACT Branch will be holding its next meeting in 2025 on Tuesday 27th May in person and via Zoom. There will be the opportunity to meet for dinner afterwards in Canberra City.

  [From collaboration with Tasha Riley, Troy Meston, Chesley Cutler, Brittany McCormack, Eun-Ji Amy Kim, Sonal Nakar & Daniela Vasco (GIER). Funded by an Education Horizon grant, Queensland Department of Education]

  Our work on the Weaving Stories of Strength project aimed to understand how to support teachers, who have professional obligations to incorporate Indigenous perspectives in their teaching. They face several challenges, including Western-centric priorities in schools, which means that Australian students may not be gaining the benefits of Indigenous knowledge. We combined research methods—Indigenous and Western—qualitative and some with quantitative origins—to reveal practical ways to help teachers build confidence when incorporating Indigenous knowledge into classrooms. Overall, our findings highlighted the importance of listening to Indigenous voices, so that schools may promote intercultural understanding and meet the diverse needs of learners.

  Today, Samantha Low-Choy will unpack how statistical thinking influenced the methodology, illustrated using a few diagrams summarising some stories of strength. These diagrams emerged from our analysis of yarns with 16 Indigenous educators from Australia, New Zealand, Canada, and the United States. Here she hints at the work underlying these diagrams: mixed and multi-methods combining method/ologies for systematic literature review*, yarning, expert elicitation*, thematic analysis, concept mapping*, all embedded within a 4R’s Indigenous Research Methods framework. Notably, the statistical thinking involved in this project is not overtly statistical, but instead reflects the somewhat “hidden” facets of statistical thinking, which were applied to help capture meanings expressed using words rather than numbers.

  The presentation will be quite interactive, so it may take 30 – 45 minutes, depending on the number and intensity of questions during/after the talk, which are very welcome!

  Core Reference

  Tasha Riley, Troy Meston, Chesley Cutler, Samantha Low-Choy, Brittany A. McCormack, Eun-Ji Amy Kim, Sonal Nakar, Daniela Vasco (2024). Weaving stories of strength: Ethically integrating Indigenous content in Teacher education and professional development programmes, Teaching and Teacher Education, 142: 104513, 14pp.

  Biography: Samantha Low-Choy, Senior Biostatistician, Stillbirth Centre of Research Excellence, Mater Research Institute—University of Queensland and Adjunct Associate Professor, Griffith Institute of Education Research (GIER), Griffith University

  Sama recently joined Mater Research Institute—University of Queensland, as senior biostatistician across the Stillbirth Centre of Excellence and the Genesis perinatal research team in Mater Hospital. This continues a career-long tendency to collaborate with researchers to answer their questions, typically in the realm of applied statistics, with occasional excursions into computation. This builds on experience in university research hubs to help researchers better understand and apply statistical methods, at Bond University, QUT, and Griffith University. She’s also worked outside the higher education system, working in Queensland’s EPA and the CRC on national plant biosecurity.

  Her contributions have spanned several fields, with highly cited and/or impactful publications in ecology, environment, psychology, education, criminology, and health. Sama’s main research interests—on novel applications or methodology in the statistical realm—lie in conceptual modelling and causal science, Bayesian statistical modelling and modelling complex systems. This includes working in the “borderlands” where statistical methods overlap with other paradigms, such as mixed (qualitative and quantitative) methods, finding structured ways to elicit expert knowledge, and multiversing.

  Please forward to any non-members who may be interested.

  Zoom link:

  https://anu.zoom.us/j/87542671367?pwd=QwDV4eb9Wos6kWoaAogZta1Ut3UxYW.1

  The zoom link will be open at 5.30pm. RSVP is not required. Full zoom details given at the end of the email.

  Dinner:

  After the talk we will be holding a dinner at 7.15pm at Banana Leaf Restaurant, 2 Akuna Street, Canberra City (Banana Leaf)

  If you are interested in attending the dinner, please let us know by 5pm Monday 26 May by entering your details at SSA Canberra Branch dinner attendance sheet or contacting Luca Maestrini (luca.maestrini@anu.edu.au ; 0415 609 961). 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 Luca (0415 609 961).

  NOTE: We are offering discounts to SSA early career and student members who attend dinner! For this meeting, dinners will be a fixed charge of $10 for student members and $20 for early career members.

  Zoom link:

  Topic: SSA ACT branch meeting
  Time: May 27, 2025 05:45 PM Canberra, Melbourne, Sydney
  
  Join Zoom Meeting
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  Password: 697400
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• National Speaker Series Hosted by Vic & Tas Branch: Experimenting for Innovation: How Data Science Drives Feature Development at Canva

  • When
    28 May 2025
  •  
    12:30 PM - 1:30 PM
  • Location
    Online

  Register

  The Statistical Society of Australia's branches have come together to launch the National Branch Lecture Series, bringing you insightful talks from experts across the country. Each month, a different branch will host a webinar, showcasing diverse topics in statistics and data science. We’re excited to invite you to this month’s session, hosted by the Vic & Tas Branch.

  Sarah Hunt will talk about how she uses experimental design to test new software features and give an example of a deep dive analysis.

  Bio: Sarah Hunt, Data Scientist at Canva.

  Key takeaways: Understand the kind of work done by a data scientist in a company.

  Show details
• CPD 198-Text Analysis with Large Language Models

  • Start
    3 Jun 2025
  • End
    4 Jun 2025
  • Location
    Online- 1:00pm- 5:00pm each day

  Register

  The SSA proudly presents Text Analysis with Large Language Models by Dr Emi Tanaka.  

  Unstructured text data are often hard to process downstream by traditional statistical methods without processing it to a structured or standardised form. In this workshop, we discuss methods to process text data such as cleaning text entries, sentiment analysis, topic identification, topic modelling, and text summarisation. This workshop also serves as an introduction to large language models (LLMs) with demonstration of LLM-assisted text analysis. The workshop will help participants understand how LLMs can be integrated into existing workflows with hands-on experience. Practical applications will be demonstrated through R using OpenAI LLMs or local Ollama models. Participants will have access to all the slides and code used in the demonstration, so you can replicate the analyses and continue exploring LLMs on your own machines.

  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.

  Required:

  - Proficient in R programming basics,

  - Own laptop/desktop with admin access and Zoom,

  - Stable internet access, and

  - Installation of Ollama (https://ollama.com) OR a developer account on OpenAI (https://platform.openai.com/) with some small credit, say US$5 (see Billing under Your profile).

  Desirable:

  - Prior experience or knowledge of machine learning methods.

  - Basics of text analysis.

  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
• CPD 196-Streamline Your Workflow: Effectively Managing Projects, Time, and Emails

  • When
    5 Jun 2025
  •  
    12:00 PM - 1:00 PM
  • Location
    Online

  Register

  Join us for the Professional Skills for Statisticians series, hosted by the SSA Mentoring Program. This professional development series is invaluable to statisticians who are looking to improve and enhance their skills in communication, time and project management. You can attend individual workshops or enrol for the full series at a discounted rate.

  Ready to supercharge your productivity? Join Emily for a session on managing projects, your time and your emails. Emily will share strategies to rethink how you work, how to prioritise your tasks, and share tips and tricks to organize your workload, meet deadlines, and manage emails. Whether you're just starting out, working in academia, or industry, this session is sure to provide some insights to help improve your workflow.

  Presenter: A/Professor Emily Karahalios, University of Melbourne

  Emily is a biostatistician in the Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne. Emily is the Deputy Head of the Biostatistics Unit in the Centre, a senior biostatistician in the Methods and Implementation Support for Clinical and Health research Hub (MISCH), and coordinator for the Master of Biostatistics courses at the University of Melbourne. Emily’s role as a teaching, research and collaborating statistician has led her to find ways to improve her workflow and manage her time, and she has been sharing her tips with others for several years.
  

  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
• Personal Journey Of Eric Sowey: A Webinar by Early Career & Student Statisticians Network and History Standing Committee of SSA, in collaboration with the NSW Branch.

  • When
    5 Jun 2025
  •  
    2:00 PM - 3:00 PM
  • Location
    online

  Register

  Personal Journey Of Eric Sowey: A Webinar by Early Career & Student Statisticians Network and History Standing Committee of SSA.

  This is the fifth in the series of webinars that focus on the personal journey of older Australian statisticians who have made a difference. 

  Eric will present his personal journey in four vignettes. He will speak to each of these, drawing out some memorable experiences and what he learned from them. His choice of stories will be guided by what he expects people will find of interest as they prepare for, or launch, their careers in statistics-related fields.

  The four vignettes he will present are:

  1. The attractions of intellectual discovery in a multi-disciplinary field.

  2. The rewards of educating others.

  3. Making academia a better place within my sphere of influence.

  4. My professional life is not all my life.

  BIO: Eric Sowey

  
  

  Eric Sowey is a widely experienced scholar with a passion for interdisciplinary research and for teaching excellence. His academic journey corresponds to a 40 year career built on a deep commitment to intellectual integrity in both academic research and professional practice.

  An esteemed educator, recognised by a UNSW Vice-Chancellor's Award for Excellence in Teaching, Eric pioneered innovative approaches to teaching statistics for long-term retention of learning.

  For those to whom statistics is more than a tool for solving technical problems, Eric (together with Peter Petocz) wrote A Panorama of Statistics. Their intent is to highlight a variety of engaging and quirky facets of statistics and let readers discover their fascinations.

  During a decade of service on the Academic Board of UNSW, Eric worked collaboratively to enhance undergraduate education institution-wide.

  Outside academia, Eric finds many fulfilments as a spouse and a parent of two children. Beyond his professional accomplishments, his personal interests and community volunteering have contributed much to a well-rounded life.

  Why Attend?

  Learn from Experience: Eric's career path offers invaluable lessons for aspiring statisticians and educators.

  Contribute to History: This webinar will be recorded, with a transcript prepared to support the History Standing Committee's efforts in documenting the evolution of statistics education in Australia.

  Who Should Attend?

  ·        Early career statisticians

  ·        Students aspiring in statistics and related fields

  ·        Anyone interested in the history and development of statistics education

  
  

  Show details
• CPD 197-Tips for Interview Success

  • When
    19 Jun 2025
  •  
    12:00 PM - 1:00 PM
  • Location
    Online

  Register

  Join us for the Professional Skills for Statisticians series, hosted by the SSA Mentoring Program. This professional development series is invaluable to statisticians who are looking to improve and enhance their skills in communication, time and project management. 

  Effective communication and preparation are both essential to excel in job interviews. In this presentation, we will cover key preparation techniques tailored for statisticians, including thorough research on potential employers and crafting compelling responses to common technical and behavioural questions. The talk will emphasize how to effectively communicate complex statistical concepts to both technical and non-technical interviewers. We'll explore strategies for showcasing your analytical skills, discussing your experience with statistical software and programming languages, and presenting your past projects or research. Additionally, the presentation will cover how to align your statistical training and work experience with specific job requirements, demonstrating your value to potential employers.

  Presenters: Julie Simpson and Katrina Scurrah

  Julie is Head of Biostatistics at the Melbourne School of Population and Global Health and Director of the Methods and Implementation Support for Clinical and Health research (MISCH) Hub at the University of Melbourne. She has 30 years’ experience collaborating on multidisciplinary research projects with clinicians, laboratory scientists, epidemiologists and health policy-makers at universities and hospitals worldwide. Throughout her career she has sat on many interview panels for statistics positions based at Universities, hospitals and research institutes.

  Katrina is the Research and Analysis Team Lead for Ten to Men: The Australian Longitudinal Study on Male Health, at the Australian Institute of Family Studies, which is a Federal Government statutory agency. She has 25 years of experience in the development and application of statistical models for complex data, especially data obtained from twins, siblings, families and linked administrative databases. Her work aims to improve the health and wellbeing of individuals and families through evidence-based research. She has a strong interest in capacity building in health and medical research through statistical consulting, collaborating, research facilitation, educating, and mentoring.

  
  

  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
• CPD 202- Take a Data Plot and Make It Better presented by Dianne Cook

  • When
    20 Jun 2025
  •  
    1:00 PM - 4:30 PM
  • Location
    Online
  • Spaces left
    10

  Register

  Part of the Statistical Computing and Data Visualisation Section tutorial series
  

  Take a Data Plot and Make It Better presented by Dianne Cook

  

  This tutorial is for data analysts and statisticians who work regularly with data and want to improve their ability to make effective data visualisations. You will learn general principles that can get you off to a good start in making a data plot, and how to use these to layer up to a more effective communication. It will be hands-on, so we will code together and make the plots and improve them. There will be an opportunity to bring your own plot and data, and work together on making it better.

  Bio: Dianne Cook

  Dianne Cook, a Professor of Statistics at Monash University in Melbourne, Australia, is a global leader in data visualisation. She has delivered over 100 invited talks internationally and published extensively on various aspects of data visualisation. Dr. Cook is a Fellow of the American Statistical Association, an elected member of the International Statistical Institute, past editor of the Journal of Computational and Graphical Statistics, and the R Journal. She has served as a Board Member of the R Foundation and is currently the co-chair of the Statistical Computing and Visualisation Section of the Statistical Society of Australia

  Requirements:

  You should have a basic understanding of R, be familiar with tidy data, and know how to use ggplot2. It’s also helpful if you’ve read the material in R4DS

  and taken a first-year statistics course.

  Structure of the tutorial:

  length (mins)	topic	description
  5	Overview	What we will cover
  10	Tidy data	Make the data do the work to more easily create a plot
  20	Grammar of graphics	Defining a plot succinctly and clearly
  15	Guided exercises
  15	Cognitive principles	Equipping your toolbox to work for many purposes
  15	Guided exercises
  10	Identifying poor elements	Develop skills in identifying what can be improved in a plot
  30	BREAK
  15	Fixing the plot design	Practicing improving a plot based on cognitive principles, tidy data and the grammar of graphics
  10	Guided exercises
  15	Styling and theming	Common ways to polish a plot or ensemble of plots
  10	Guided exercises
  10	Is the pattern visible and real	Check what you are trying to communicate, using statistical thinking
  10	Guided exercises
  20	Making your own plot better	Your turn to have a guided practice at improving a plot from your own work

  
  

  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 a $25 administration fee. 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-188-Item Nonresponse and Imputation

  • Start
    24 Jun 2025
  •  
    5:00 PM
  • End
    15 Jul 2025
  • Location
    Online- Weekly 1 hour meetings taking place Tuesdays
  • Spaces left
    13

  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.
  

   Topics:

  1. Introduction & Missing Data Mechanisms

  2. Default Strategies of (Not) Dealing with Missing Data and Their Implications

  3. Common Misconceptions Regarding Imputation & Basic Imputation Methods

  4. More Advanced Imputation Methods & Multiple Imputation

  Timeframe:

  June 24 – July 15, 2025. Weekly Meetings taking place Tuesdays, 5:00 – 6:00 pm AEST

  Course Objectives

   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.

  Your instructor: Instructor Prof. Dr. Jörg Drechlser  

  Current positions:

  ▪ Interim head of the Department for Statistical Methods at the Institute for Employment Research, Germany

  ▪ Associate Research Professor, Joint Program in Survey Methodology, University of Maryland ▪ Honorary Professor, University of Mannheim

  Teaching engagements:

  • Instructor for three different courses in the International Program in Survey and Data Science

  • Regular short courses for various institutions and universities on data confidentiality and synthetic data

  Research areas:

  ▪ Missing data, imputation, data confidentiality

  Prerequisites

   ▪ Students should be familiar with generalized linear models and basic probability theory.

  ▪ The statistical software R will be used for illustrations and for (some of) the homework assignments. Thus, basic knowledge of R is required to be able to complete the assignments.

   Grading will be based on:

  ▪ 2 online quizzes

  ▪ 2 homework assignments

  ▪ Participation in weekly meetings & engagement in discussion forums

  ▪ Final online exam

  Early Bird Deadline
  Please book before 30 April 2025 to take advantage of the Early Bird Deadline.

  Prices include GST.
  

  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
• National Speaker Series Hosted by QLD Branch: Estimating Size of Hidden Populations in Sensitive Contexts: Applications in HIV, Reproductive Health, and Mental Health- Lessons from Iran

  • When
    27 Jun 2025
  •  
    11:00 AM - 12:00 PM
  • Location
    Online

  Register

  The Statistical Society of Australia's branches have come together to launch the National Branch Lecture Series, bringing you insightful talks from experts across the country. Each month, a different branch will host a webinar, showcasing diverse topics in statistics and data science. We’re excited to invite you to this month’s session, hosted by the Queensland Branch.

  Population size estimation of hard-to-reach populations (e.g., female sex workers, people who inject drugs, and men who have sex with men) is critical for informing HIV policy, guiding resource allocation, and evaluating the impact of prevention and treatment programs. However, due to stigma, legal constraints, and social norms, these populations often remain hidden, making conventional survey approaches unreliable. The challenge of size estimation also extends beyond the context of HIV, applying to other sensitive and stigmatized behaviors such as intentional abortion, gender transition, and self-harm.

  Drawing on over a decade of methodological and field research from Iran, this talk presents a comparative overview of direct and indirect approaches to population size estimation. Direct methods, such as capture-recapture, multiplier, and truncated Poisson models, are explored through concrete case studies, highlighting how administrative records, clinic-based data, and judicial registries can be leveraged in constrained environments. Indirect methods—including the cross-wise model, single sample count, proxy respondent, and network scale-up—are discussed in terms of their statistical assumptions and implementation logistics. This overview aims to share not only technical insights but also practical experiences, illustrating the trade-offs between accuracy and feasibility in contexts where direct questioning may be neither safe nor effective.

  Biography: Dr Mohammad Reza Baneshi

  

  Dr Mohammad Reza Baneshi is a biostatistician and Research Fellow at the Australian Women and Girls’ Health Research (AWaGHR) Centre and the School of Public Health at The University of Queensland. Since joining UQ in 2020, his research has focused on longitudinal data analysis and advancing methodological approaches in studies of multimorbidity across the life course. Before relocating to Australia, Dr Baneshi led several national studies in Iran to estimate the size of hidden and stigmatized populations, such as sex workers, people who inject drugs, and transgender individuals in Iran. These studies provided essential evidence for the Iranian Ministry of Health and Medical Education and were directly used to guide national policy and program planning. He has authored over 180 peer-reviewed publications and co-authored two reference books. Dr Baneshi has also served as a consultant of the WHO to assess the practicality of size estimation methods in the Middle East and North Africa (MENA) region. 

  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

  
  

  Show details
• CPD 189-Step-by-Step in Survey Weighting

  • Start
    14 Aug 2025
  •  
    4:00 PM
  • End
    4 Sep 2025
  • Location
    Online- Weekly 1 hour meetings taking place Thursdays
  • Spaces left
    14

  Register

  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.
  

   Topics:

   1. Basic Steps in Weighting 

  2. Basic Steps in Weighting (continued) 

  3. Calibration and Other Uses of Auxiliary Data in Weighting

  4.  Calibration (continued) and Replicate Weights

  Timeframe:

  August 14 – September 4, 2025. Weekly Meetings taking place Thursdays, 4:00- 5:00 pm AEST.

  Course Objectives

   

  By the end of the course, participants will have learned… ▪ The role of survey weights in population inference. ▪ Steps in weighting, including computation of base weights, nonresponse adjustments, and uses of auxiliary data. ▪ Nonresponse adjustment alternatives, including weighting cell adjustments, formation of cells using classification algorithms, and propensity score adjustments. ▪ Weighting via poststratification, raking, general regression estimation, and other types of calibration. ▪ How to assess if weights are not needed.

  Your instructor: Anna-Carolina Haensch 

  Current positions:

  ▪ Assistant Research Professor at University of Maryland

  ▪ Lecturer (Akademische Rätin) at LMU Munich

  Teaching engagements:

  ▪ Review of Statistical Concepts (IPSDS)

  ▪ Introduction to Machine Learning Techniques (GESIS Summer School)

  ▪ Introduction to Statistics and Data Science (LMU)

  Research areas:

  ▪ Synthetic Data

  ▪ Survey Sampling

  ▪ Missing Data

  Prerequisites

  ▪ Sampling theory,Applied sampling.

  ▪ Some experience with variance estimation and statistical analysis using survey data will be helpful.

  ▪ Intermediate knowledge of the R statistical computing software

   Grading will be based on:

   ▪ 4 Homework assignments(50% of grade)

  ▪ A take-home final exam (30% of grade)

  ▪ Class Participation (20% of grade) in discussion during the weekly online meetings and posting questions to the weekly discussion forum (deadline: 24 hours before class) demonstrating understanding of the required readings and video lectures

  Early Bird Deadline
  Please book before 30 May2025 to take advantage of the Early Bird Deadline.

  Prices include GST.
  

  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 190-Introduction to Big Data & Machine Learning

  • Start
    26 Aug 2025
  •  
    9:30 AM
  • End
    16 Sep 2025
  • Location
    Online- Weekly 1 hour meetings taking place Tuesday
  • Spaces left
    14

  Register

  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.
  

   Topics:

    1. Overview of Big Data; Working with Big Data, Classical Statistical Approaches vs. Statistical Machine Learning

  2. Model Evaluation/Validation, K-Means Clustering

  3. Nearest Neighbors, CARTS

  4.   Random Forests

  Timeframe:

  August 26 – September 16, 2025. Weekly Meetings taking place Tuesdays, 9:30 - 10:30 am AEST.

  Course Objectives

   

  This course covers… ▪ an overview of key Big Data terminology and concepts ▪ an introduction to common data generating processes ▪ a discussion of some primary issues with linking Big Data with Survey Data ▪ issues of coverage and measurement errors within the Big Data context ▪ inference versus prediction ▪ general concepts from machine learning including signal detection and information extraction ▪ potential pitfalls for inference from Big Data ▪ key analytic techniques (e.g. classification trees, random forests, conditional forests) to process Big Data using R with example code provided

  Your instructor: Prof. Trent Buskirk 

  Current positions:

  ▪ Novak Family Professor of Data Science and Chair of the Applied Statistics and Operations Research Department 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

  No prerequisites.

  We recommend a good understanding of the material typically taught in undergraduate statistics courses and some familiarity with regression techniques. While not a prerequisite, familiarity with the R software package (base R or R using Rstudio) is strongly encouraged.

   Grading will be based on:

  ▪ 4 online quizzes (worth 5% each)

  ▪ Participation in discussion during the weekly online meetings and submission of questions to the weekly discussion forums demonstrating understanding of the required readings and video lectures (20% of grade).

  ▪ 3 homework assignments (worth 20% each)

  Early Bird Deadline

  Please book before 30 June.2025 to take advantage of the Early Bird Deadline.

  Prices includes GST.
  

  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 191-Machine Learning II

  • Start
    14 Oct 2025
  • End
    2 Dec 2025
  • Location
    Online- Weekly 1 hour meetings taking place Tuesday
  • Spaces left
    15

  Register

  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.
  

   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

  Timeframe:

  October 14 – December 2, 2025. Tentative Weekly Meetings as follows (exact dates and times TBC):

  ▪ Week 1: Tuesday, October 14, 9:00 – 10:00 am AEDT

  ▪ Week 2: Tuesday, October 21, 6:00 – 7:00 pm AEDT

  ▪ Week 3: Tuesday, October 28, 6:00 – 7:00 pm AEDT

  ▪ Week 4: Tuesday, November 4, 6:00 – 7:00 pm AEDT

  ▪ Week 5: Tuesday November 11, 11:00 am – 12:00 pm AEDT

  ▪ Week 6: Tuesday November 18, 11:00 am – 12:00 pm AEDT

  ▪ Week 7: Tuesday, November 25, 11:00 am – 12:00 pm AEDT

  ▪ Week 8: Tuesday, December 2, 9:00 – 10:00 am AEDT

  Course Objectives

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

  Your instructor: Prof. Trent Buskirk 

  Current positions:

  ▪ Novak Family Professor of Data Science and Chair of the Applied Statistics and Operations Research Department 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.

  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
  

  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

  ▪ Random forests

  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 homework assignments (10% each)

  ▪ 8 online quizzes (5% each)

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

  Early Bird Deadline

  Please book before 15 August 2025 to take advantage of the Early Bird Deadline.

  Prices include GST. There is also a discount of $150 for Machine Learning II if registering at the same time as Introduction to Big Data & Machine Learning or have completed Introduction to Big Data & Machine Learning in the past.
  

  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
• 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
• ASC2025

  • Start
    1 Dec 2025
  • End
    5 Dec 2025
  • Location
    Curtin University, Perth, WA

  Register

  

  Curtin University, Perth, WA

  1–5 December

  
  

  ASC2025 brings together statisticians, data scientists, and professionals from academia, government and industry to explore the latest in statistical thinking and practice.

  Hosted by the Statistical Society of Australia, the conference will feature keynotes, contributed talks, panel sessions and workshops—covering cutting-edge research, practical applications and real-world challenges.

  Whether you're an early career statistician or an experienced professional, ASC2025 is a chance to learn, connect and collaborate with colleagues from across Australia and beyond.

  
  

  Now open! Early Bird registration for ASC2025

  We’re thrilled to announce that registration for ASC2025 is officially open! Join us this December for an exciting program featuring inspiring keynote speakers, expert-led sessions, hands-on workshops and plenty of opportunities to connect with peers and leaders in the field.

  Your registration fee includes morning tea, lunch, afternoon tea and entry to the welcome reception on Day 1. Please note that conference dinner tickets must be purchased separately. Don’t miss out! Early Bird pricing ends on 31 August 2025.

  
  

  Registration Information

  
  

  Individual & Multiple Registrations

  If you would like to process multiple registrations, you will need to register each person separately. This is important to capture a record of each individual's attendance at the conference as well as their correct contact details. If you have any questions, please email events@statsoc.org.au .

  Statistical Education Symposium

  As part of the broader ASC2025 program, a series of sessions dedicated to statistics and data science education will take place across Thursday and Friday of conference week. On Thursday, statistical education will feature prominently within the main conference program. Friday will be fully dedicated to special sessions organised by the SSA’s Statistical Education Section.

  Conference dinner & tickets

  Join us for an evening on Wednesday, 3 December at the Australian Statistical Conference Dinner. This is a great opportunity to connect with fellow delegates, network with peers, and enjoy a delicious dinner. The conference dinner is not included in the conference registration fee. Tickets can be purchased after selecting your conference registration. Each delegate may purchase one ticket for themselves and one for a guest through the registration portal. More information including venue will be available soon. Please email events@statsoc.org.au for multiple tickets.

  Conference Workshops & Social Tours 

  Information on conference workshops and social tours will be available soon. All SSA members and registered participants will be notified as soon as details are released.

  Cancellation Policy

  Refunds: Cancellations made more than two weeks before the event are eligible for a refund, minus: Stripe processing fee: 1.75% + $0.30 per transaction and SSA administration fee: $20. No refunds will be issued for cancellations made within two weeks of the event.

  Transfer of Registration: Registrations can be transferred to another person within the same organisation at any time. Please notify changes via email: events@statsoc.org.au .

  Show details
• ICOTS -12th International Conference on Teaching Statistics

  • Start
    12 Jul 2026
  •  
  • End
    17 Jul 2026
  •  
  • Location
    Brisbane Convention & Exhibition Centre (BCEC)

  The theme for ICOTS 12 is What? Who? When? How? Asking questions is fundamental to good statistical practice, including good practice in statistical education, and these questions reach across all facets and contexts of the teaching of statistics and data science. Technology opens doors to tackling more and more complex problems and data, and although there is no magic solution to all the teaching challenges this poses, the statistical and data science education community needs to bring collaborative and collective wisdom, analysis and research to the what, who, when and how.

  The first call for abstracts is now open for paper proposals to be featured under Main Topics 1-10.

  See Home • ICOTS 12 for Main Topics (under Scientific Programme) and for Submissions and Important dates under Notices and Guidelines.

  
  

  Show details