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• Personal Journey Of Ann Eyland: A Webinar by Early Career & Student Statisticians Network and History Standing Committee of SSA

  • When
    26 Nov 2024
  •  
    2:30 PM - 3:30 PM
  • Location
    online

  Register

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

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

  

  Bio-ANN EYLAND

  Shortly after I was born, my family moved to Townsville North Queensland as my father took up appointment as Headmaster of The Townsville Grammar School. My father taught mathematics. He graduated in Mathematics and Latin from the University of Queensland as an external student. My mother was the first female member of her family to work. We returned to Sydney when I was in Primary School. I was very fortunate to go to an opportunity school, and on to a selective high school.

  I graduated with Honours in Pure Mathematics and a Master’s degree by research from Sydney University. My doctorate was completed at the University of Aberdeen under the supervision of A W F Edwards, a population geneticist, who was one of R A Fisher’s last Ph D students.

  On returning to Sydney, for 4 years I was a Senior Tutor in Mathematical Statistics at Sydney University, and then I joined the Statistics staff at Macquarie University where I stayed for 18 years. Statistics allowed me to play in other people’s backyards. I think I re-invented myself every 7 years or so. Consulting work across many disciplines created interesting and demanding opportunities, the most significant of which was management of the University’s Equal Opportunity Project. This led to a deep interest in Labour Economics and membership of University committees that affect staffing policy.

  University life for me always involved more than teaching and research. It all began in my Honours year when I became a member of the Board of the Sydney University Women’s Union. I have served on the governing bodies of both Macquarie and Sydney Universities as well as the Statistical Society at both State and Federal levels.

  After 18 years, I left Macquarie to become Principal of the Women’s College at Sydney University and then Principal Researcher Statistics and Design at the NSW Law Foundation.

  I am happily retired and spend time learning about Art. Architecture and Photography and cooking!

  
  

  What to Expect:

  Interview Session: Conducted by Ayse Bilgin, History Committee member, Ann will share her journey from academic researcher in pure mathematics to influential statistician and university leader. Her career spans interdisciplinary consulting, significant contributions to university staffing policy, and leadership roles, including Principal of the Women’s College at Sydney University and Principal Researcher in Statistics at the NSW Law Foundation.
  
  Q & A Session: Following the interview, engage directly with Ann. Pose questions that delve deeper into Ann’s experiences and gain insights relevant to your own career aspirations.

  Why Attend?

  Learn from Experience: Ann’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

  
  

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• SSA Vic & Tas November Social Event

  • When
    26 Nov 2024
  •  
    6:00 PM
  • Location
    Boulder Lab, 260-266 Barkly St, Brunswick AND Baba Hawker, 148 Sydney Rd, Brunswick.

  Register

  Join us for an evening of bouldering and dinner in Melbourne.

  schedule

  6:00-7:30 pm, bouldering at Boulder Lab, Brunswick.

  7:30-9 pm, dinner at Baba Hawker, Brunswick.

  You can register for one or both activities.

  cost

  Both activities are at your own cost, to be paid at the venue on the night.

  Bouldering: $22 (full price), $20 (student), $7 (shoe hire). See Boulder Lab website for full details.

  Dinner: see menu for an indication of prices.

  public transport

  Both venues are walking distance from

  • Brunswick station, Upfield train line
  • Stop 20 Barkly Square, 19 tram

  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
• SSA SA November Branch meeting - Things I've learnt the hard way about regression

  • When
    27 Nov 2024
  •  
    6:00 PM - 7:00 PM
  • Location
    University of South Australia City East, North Tce, Centenary Building, Level 3, Room C3-22

  The South Australian Branch of the Statistical Society would like to invite you to a hybrid November meeting of the 2024 program. This is both an in-person and online presentation regarding practical lessons in the use of regression by Lauren Kennedy from the University of Adelaide.

  Date: 27th November (Wednesday) 2024

  Time: 6:00 – 7:00 pm (Adelaide time) (Refreshments from 5:30 pm, Zoom access from 5:45pm)

  Venue: University of South Australia City East, North Tce, Centenary Building, Level 3, Room C3-22.

  https://unisa.edu.au/siteassets/campus-facilities/maps/city-east-campus-map.pdf

  Zoom access : Join from a PC, Mac, iOS or Android - Password: 393474: https://unisa.zoom.us/j/86046334264?pwd=eqAaHupLaJgdySTRRFvboBBnaautaC.1

  Dinner: For those who are interested, a post-meeting dinner is planned for 7:30pm at Café Michael 2, 204 Rundle St.  Please RSVP to Lan.Kelly@unisa.edu.au by 5pm Monday November 25

  
  

  Topic: Things I've learnt the hard way about regression

  Regression. It's one of our fundamental tools of the trade. Yet the world of examples we teach in class and the realities of real-world data are far apart. In this talk I share a collection of examples that are odd, interesting and sometimes counterintuitive. Based on my experiences working in prediction and post-stratification based survey inference, my examples include individual versus group prediction, logistic vs linear regression and rare events bias. During the discussion time I hope to leave space for you to share your own weird and wonderful examples. 

  
  

  Speaker biography

  Lauren is a Senior Lecturer in Statistics at the University of Adelaide. Her work focusses on survey statistics and sampling, and applied Bayesian statistics. She is particularly interested in deepening methodological understanding through applied work and consideration of the statistical workflow. 

  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
• ACT Branch Meeting -- Wilson Lecture 2024

  • When
    2 Dec 2024
  •  
    5:45 PM - 7:15 PM
  • Location
    In-person and online via Zoom

  SSA ACT branch invites everyone to attend our final meeting for 2024 calendar year, the inaugural Wilson Lecture. The lecture is in honour of the late Professor Sue Wilson and her immense contributions to the statistics and bioinformatics community across Canberra, Australia, and globally. The Wilson lecture will be run as the branch's final lecture every second year, alternating with the Knibbs lecture.

  Date: Monday 2 December 2024

  Time: Starts 5:45pm and finishes by 7:15pm    

  Venue: Haydon Allen Building HAG040, ANU (https://studentvip.com.au/anu/main/maps/142179), or via Zoom <https://anu.zoom.us/j/83946471457?pwd=bA9UC5VaOeaogA8xDEEkKZtAHPaqUH.1>

  Speaker: Gillian Heller, Professor of Biostatistics at the NHMRC Clinical Trials Centre, University of Sydney.

  Topic: Back to the future, or "Model what you measure"

  Abstract: The evolution of statistical modelling has historically been constrained by the practical limitations of computation. As increased mathematical complexity often implies more intricate computation, over time statistical models have grown both mathematically and computationally more complex; but paradoxically sometimes conceptually simpler models present more computational challenges than complex ones. I shall be discussing two well-known examples of this phenomenon.

  Biography: Gillian Heller is Professor of Biostatistics at the NHMRC Clinical Trials Centre, University of Sydney. After completing her studies at the University of Cape Town, Gillian migrated to Australia, where she has held academic positions at the University of New South Wales, Macquarie University, and the University of Sydney. She is past chair of the Biostatistics Collaboration of Australia, past Head of the Department of Statistics at Macquarie University, Honorary Professor, School of Mathematical and Physical Sciences, Macquarie University, and Honorary Member of the Statistical Modelling Society. Gillian’s research interests lie in distributional regression and biostatistics, in which she has published widely. She is co-author of four books, the first of which is on the topic of generalized linear modelling in the context of insurance, and the next three on the methodology and applications of distributional regression. She collaborates widely with colleagues in the UK and Europe. In her position at the Clinical Trials Centre, Gillian works closely with clinicians and other medical professionals, in a consulting role.

  Dinner: After the talk we will be holding a dinner at Amara Indian Restaurant, The Melbourne Building, 51-53 Northbourne Avenue, Canberra City (Amara Indian Restaurant).

  If you are interested in attending the dinner, please let me know by 6pm Friday 29 November by entering your details at SSA ACT Branch dinner attendance sheet, or contacting me (warren.muller@csiro.au; 0407 916 868). Please regard this as a firm commitment, not just an intention. For withdrawals after the deadline, please remove your name from the sheet and phone or text me (0407 916 868).

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

  ------------------

  Full Zoom Details for Wilson lecture:

  Topic: SSA ACT Wilson lecture
  Time: Dec 2, 2024 05:45 PM Canberra, Melbourne, Sydney
  
  Join Zoom Meeting
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  Meeting ID: 839 4647 1457
  Password: 502840
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• Burnet Institute SSA Vic & Tas Branch, and VicBiostats joint event, Dec 2024

  • When
    10 Dec 2024
  •  
    10:30 AM - 12:00 PM
  • Location
    Burnet Institute, Level 3 foyer, via 89 Commercial Road/Centre lane entrance

  Register

  Title: HIV cohorts and the development of methods to make causal inferences from observational data

  Speaker: Jonathan Sterne

  Biography: Jonathan Sterne is Director of the N Bristol Biomedical Research Centre, co-Director of Health Data Research UK South-West, and Professor of Medical Statistics and Epidemiology at the University of Bristol, UK. During the pandemic, he was co-lead of the UK’s Longitudinal Health and Wellbeing COVID-19 National Core Study, which linked population-scale electronic health records with highly characterised longitudinal population studies. This UK-wide collaboration produced research on COVID-19 vaccination and long COVID based on analyses of data on up to 55 million people, held within newly-created Secure Data Environments. Jonathan is Principal Investigator of the ART Cohort Collaboration of HIV cohort studies, which works closely with the HIV-CAUSAL collaboration based at the Harvard School of Public Health. 

  In-person: In-person attendants are asked to register for catering purposes (limit of 30 places).  In-person attendees to come directly to Level 3 foyer, via 89 Commercial Road/Centre lane entrance and they will be met by a Burnet Institute staff member. Registration form to please include email address and mobile, to meet Burnet Institute requirements for sign in of visitors. 10.30 am morning tea, 11am to 12pm seminar with time for questions. 
  
  In-person limited to 30 places. 

  Online meeting via zoom

  
  

  
  

  Show details
• International Statistics Conference ISC 2024

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

  
  

  Show details
• CPD 186-Sampling I

  • Start
    6 Feb 2025
  •  
    12:00 PM
  • End
    3 Apr 2025
  • Location
    Online- Weekly 1 hour meetings taking place Thursdays
  • 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. Introduction; Course Perspectives

  2.  Simple Random Sampling, Sampling Frames, and Introduction to Clustering

  3. Stratified Sampling I

  4. Stratified Sampling II, Systematic selection

  5. Cluster Sampling

  6. Unequal-Sized Clusters I

  7. Unequal-Sized Clusters II

  8. Variance Estimation

  Timeframe:

  February 6 – April 3, 2025. Weekly Meetings taking place Thursdays, 12:00 – 1:00 pm AEDT

  
  

  Course Objectives

   By the end of the course, participants will… ▪ understand the basic ideas, concepts and principles of probability sampling from an applied perspective ▪ be able to identify and appropriately apply sampling techniques to survey design problems ▪ be able to compute the sample size for a variety of sample designs ▪ understand and be able to assess the impact of the sample design on survey estimates ▪ be able to estimate the precision of the survey statistics using different estimation techniques

  
  

  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

   The course is presented at an intermediate statistical level. While we will not develop mathematical aspects of sampling theory, statistical notation and outlines of some algebraic proofs will be given. A sound background in applied statistics, proficiency in mathematics, including basic algebra, is necessary, since some algebraic derivations will be presented (although little emphasis will be placed on the derivations). A thorough understanding of the notation and algebraic results will be required.

  
  

  
  

  Grading will be based on:

  ▪ 8 Homework assignments (50% of grade)

  ▪ 8 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 6 January 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
• 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
• 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

  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. 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 ▪ beabletodesign and implement multistage sampling with different sampling techniques ▪ befamiliar 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)

  ▪ 4Quizzes (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
• 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
    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. 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
• 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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• 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
    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. 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
    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. 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 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