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    • 17 Aug 2020
    • 1:00 PM - 2:00 PM (UTC+10:00)
    • via Zoom, times are in AEST
    Register

    The Statistical Society of Australia, the Australian Bureau of Statistics and the University of Melbourne are pleased to announce the following joined webinar:

    Can multiple disparate data sources complement each other?

    The case of researching economic disadvantage in Australia

    to be held on 17 August 2020 from 1:00PM -2:00PM.

    About this webinar

    The webinar is the first in a series of two with a data integration theme. Through the lens of researching economic disadvantage in Australia, Dr. Anders Holmberg and Dr. Rajeev Samarage will talk about data quality and methodology considerations that arise when a research project uses many fundamentally different and disparate data sources.

    Often there are good reasons in research to reuse already existing data. The obvious drawback of doing so is that the data collection and content is not ideal for the problem at hand. Nevertheless, cost efficiency, adequate methodology and the possibility to use multiple data sources are factors that may compensate and encourage such research designs. This webinar discusses a systematic way to assess the benefits and improve the quality when using multiple sources in a complex research problem. The need to explain quality in such situation has increased with the trend internationally to make more data safely available to a broad range of research uses. The presented framework has a step-wise approach for researchers to make trade-offs and choose the right mix of units and variables. It also illustrates where there are demands for more statistical research. This will be highlighted in the webinar.

    About the presenters

    Dr. Anders Holmberg is the Chief Methodologist at the Australian Bureau of Statistics. He has a background working with various types of data sources for official statistics in many different countries. This include design and collection of sample survey data, use of multiple administrative data sources for population censuses and combining surveys well as administrative data of people and businesses for statistical and research purposes.

    Dr. Rajeev Samarage is the Data and Analytics Lead at the Melbourne Institute: Applied Economic and Social Research within the University of Melbourne. He has a background in engineering with data analytics experience in developing medical imaging technology. This includes data visualisation and he is currently applying his skills to data analytics in the social sciences. He is also involved in data management practices and oversees the development of MIDL (the Melbourne Institute Data Lab), a secure research facility for conducting analyses of a range of data sources including survey and administrative data.

    To register

    This is a free event, but you will need to register. Click on the button on the left to save your place. After registering, you will receive a confirmation email containing information about joining the meeting. 

    If you have any questions, please contact Marie-Louise Rankin.

    Our Guarantee
    Our goal is to provide truly exceptional offerings and service, and we won't be happy until you are. If any programs, products or services of SSA do not fulfill our promise, we will make the situation right.

    Event Cancellation or Postponement
    SSA reserves exclusive right to modify, postpone/reschedule or cancel programs for any reason, including but not limited to emergency, inclement weather or other 'acts of God'. If there is an event cancellation, every attempt will be made to reschedule, and registration fees will be applied to the rescheduled event date. Any travel, lodging, or incidental expenses incurred related to a cancelled event cannot be refunded under any circumstances. 

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    Registration and attendance at, or participation in, SSA meetings and other activities constitutes an agreement by the registrant to the use and distribution of the registrant or attendees' image or voice in photographs, videotapes, electronic reproductions and audiotapes of such events and activities by SSA. 


    • 19 Aug 2020
    • 9:30 AM (UTC+10:00)
    • 20 Aug 2020
    • 1:00 PM (UTC+10:00)

    Course Overview

    R is widely used and extremely powerful statistical software. This course assumes that you have never used R before. You will learn how to obtain and install R, which is open-source software, and RStudio, which is a versatile, user-friendly interface for using R. It is very useful to do this course before our introductory statistics course, Introductory Statistics for Researchers.

    This course will cover some basic features of R and lay the groundwork for you to improve your R skills independently. The course is self-paced and focused on developing practical skills.

    Course Requirements

    You will need a computer with course access (to install R before attending the course).

    Course 1:          Tuesday 11 & Wednesday 12 August, 2020 (two half-day sessions)

    Course 2:         Wednesday 19 & Thursday 20 August, 2020 (two half-day sessions)

    Duration: 9.30 am to 1.00 pm – Each day

    Location: Online

    For further details and bookings: 

    https://www.eventbrite.com.au/e/online-short-course-introduction-to-r-tickets-110931685658

    Stats Central provides study design and analysis support to all UNSW researchers, in collaborative and consultative roles, and conducts short courses and monthly seminars on topical issues. Please see below for our upcoming seminar and short courses. Please feel free to circulate this email to your colleagues, staff, researchers and students, who may be interested. Should you have any questions please don’t hesitate to contact us or visit our website statscentral.unsw.edu.au.

    **Due to the COVID-19 situation, we are offering online course with 20% discounted rates.**

    Note: The courses will be delivered remotely using online collaborative teaching tools, with a mix of live video-assisted lectures and computer-based tutorials. A continuous chat session will be available and there will be extra staff to answer questions during the course.

    • 19 Aug 2020
    • 6:00 PM - 7:00 PM (UTC+09:30)
    • virtual Zoom meeting

    Branch Meeting - Wednesday, 19th August 2020

    The South Australian Branch of the Statistical Society would like to invite you to the August meeting of the 2020 program.

    Virtual Venue: Join the Zoom meeting using your PC or device https://unisa.zoom.us/j/93416975159?pwd=eWU4aWo5MjZTZ3YwajlRekd6ekhaZz09 
    Password: 718170

    or Join from dial-in phone line:  Dial: +61 2 8015 2088

    Meeting ID: 934 1697 5159


    Speaker: A/Prof Nicole Pratt, University of South Australia

    Topic: A LEGENDARY way to do observational data analysis at scale!

    Abstract

    Objectives: Evidence derived from existing healthcare data including administrative claims and electronic health records can fill evidence gaps in medicine, but is often criticized due to the potential for observational study bias, for example due to residual confounding. Other concerns include p-hacking and publication bias. Here we detail a set of principles embodying a new paradigm for observational research aimed at addressing these concerns, and describe a generic implementation of these principles.

    Materials and Methods: The Observational Health Data Sciences and Informatics (OHDSI) collaborative launced the Large-Scale Evidence Generation and Evaluation across a Network of Databases (LEGEND) research initiative, aiming to generate evidence on the effects of medical interventions using observational healthcare databases. We define ten principles of LEGEND, prescribing the generation and dissemination of evidence on many research questions at once, for example comparing all treatments for a disease for many outcomes, thus preventing publication bias. These questions are answered using a prespecified and systematic approach, avoiding p-hacking. Best-practice methods address measured confounding, and control questions (questions where the answer is known) quantify potential residual bias. Finally, the evidence is generated in a network of databases to assess consistency, by sharing open source analytics code to enhance transparency and reproducibility, but without sharing patient-level information, ensuring patient privacy.

    Discussion: Following guiding principles addressing study bias, p-hacking, and publication bias, LEGEND seeks to generate reliable evidence from existing healthcare data. The principles of LEGEND will be highlighted using an example study on effects of antihypertensives, evaluating internal and external validity of the generated evidence.

    Biography

    A/Prof Pratt is an expert in biostatistics and pharmaco-epidemiology, specialising in the development of methodologies to study the effects of medicines and medical devices in linked health-care datasets. Nicole made significant contributions to medication safety surveillance, developing analysis software and pioneering a distributed network model to allow it to be implemented globally. Her research includes knowledge generation and quantification of harms from medicines and devices and has led to TGA safety warnings, changes in practice and changed guidance for medicine use. For the last five years Nicole has worked collaboratively with OHDSI (Observational Health Data Sciences and Informatics) and has helped to develop a comprehensive framework for analysing observational healthcare data at-scale. LEGEND (Large-scale Evidence Generation across a Network of Database) aims to generate real world evidence on the effects of medical interventions using best-practice statistical methodology to support clinical decision making.

    Feel free to forward this meeting notice to colleagues, all welcome.


    • 20 Aug 2020
    • 6:00 PM - 7:00 PM (UTC+10:00)
    • via Zoom, times stated are AEST


    ACEMS is proud to host a National Science Week Virtual Quiz on Thursday, 20 August from 6 - 7 pm AEST. It will be 60 minutes of fascinating and intriguing science that promises to be fun for everyone to enjoy! While the panel ponders the series of scientific questions posed to them, we're offering you the chance to test your knowledge and win some great prize packs. We hope that it may be of interest to your members and if possible it would be wonderful if you could promote it in your channels and ENewsletter.

    The event is hosted by ACEMS' Anthony Mays and  he will be joined by a great panel including 

    • Dr Gary Beane is a Research Fellow at Monash University and the ARC Centre of Excellence in Future Low-Energy Electronics Technologies (FLEET).
    • Professor Jared Cole is a Theoretical Physicist and Chief Investigator with the ARC Centre of Excellence in Exciton Science at RMIT.
    • Dr Rheanna Mainzer is a Postdoctoral Research Fellow in Biostatistics and Data Science at the Murdoch Children's Research Institute.
    • Dr Jen Martin founded and leads The University of Melbourne's acclaimed Science Communication Teaching Program and is a member of the Homeward Bound Teaching Faculty.
    • Tom Gordon studied Astrophysics, Science Communication, Space Science and Education and is a Senior Science Communicator at the School of Physics at The University of Sydney.

    The Quiz will be delivered by Zoom Webinar, to register click here.

    Kind regards

    Rosanna Verde | Outreach Business Officer | ACEMS

    Australian Research Council Centre of Excellence in Mathematical and Statistical Frontiers

    • 24 Aug 2020
    • (UTC+10:00)
    • 26 Aug 2020
    • (UTC+10:00)
    • Gold Coast, Australia

    Imagine the benefit you would get from joining a group of 50 peers - who share your biggest challenges - to share stories, network and exchange mission critical information you won’t get anywhere else. Here’s a taste of what you can expect to learn about at the Data & Analytics Leaders Exchange:

    - Developing An Enterprise-Wide Data Governance Strategy And Architecture
    - Enabling Data-Driven Decision Making Across The Business
    - Building Organisational Capability For Advanced Analytics
    - Attracting, Retaining, And Up-Skilling Staff For Digitalisation And Technological Developments
    - Maintaining Compliance With GDPR
    - Improving Business Function By Effectively Leveraging Data Insights

    Request an invite

     


    • 24 Aug 2020
    • 9:00 AM (UTC+10:00)
    • 27 Aug 2020
    • 1:00 PM (UTC+10:00)

    Introductory Statistics for Researchers

    Course Overview

    In many disciplines, researchers wishing to publish are asked to provide a rigorous statistical analysis. Reviewers are often specific about what statistical measures they want included. "Why wasn't Fisher's Exact Test used?" "Was an appropriate sample size determined a priori?" 

    How does one decide which statistical procedure is the most appropriate? What do all the sections of the output mean? 

    This course is designed as an introduction to statistical analysis for researchers. There is emphasis on understanding the concepts of statistical procedures (with a minimum of mathematics, although some will be discussed) and on interpreting computer output. This course is designed to help you, the researcher. It is helpful if you have done an undergraduate statistics subject, although this course can serve as a first introduction or a refresher. The theory behind the statistical procedures outlined in the course will, in general, not be discussed. 

    Statistical analyses require specialised software to perform calculations. In this course, we use the free statistical program R, although researchers may have another statistical package available to them. 

    A range of statistical analyses will be discussed in the course, as described in the course outline below. We will talk through examples of all analysis types and will demonstrate how to carry them out in R. Equal emphasis will also be put on interpreting the output of these analyses. There will be plenty of practical work in the course. You will need basic R proficiency to carry out the practical work; we will teach only the additional R commands needed for these analyses. 

    Course Requirements

    You will need to use a computer during the course. You will also need administrator rights to install software needed for the course onto your computer. Previous basic experience using the program R is essential. 

    Date:               Monday 24 to Thursday 27 August, 2020 (four half-day sessions)

    Duration:         9.00 am to 1.00 pm – Each day

    Location:         Online

    For further details and bookings:

    https://www.eventbrite.com.au/e/online-short-course-introductory-statistics-for-researchers-tickets-112412669320

    Stats Central provides study design and analysis support to all UNSW researchers, in collaborative and consultative roles, and conducts short courses and monthly seminars on topical issues. Please see below for our upcoming seminar and short courses. Please feel free to circulate this email to your colleagues, staff, researchers and students, who may be interested. Should you have any questions please don’t hesitate to contact us or visit our website statscentral.unsw.edu.au.

    **Due to the COVID-19 situation, we are offering online course with 20% discounted rates.**

    Note: The courses will be delivered remotely using online collaborative teaching tools, with a mix of live video-assisted lectures and computer-based tutorials. A continuous chat session will be available and there will be extra staff to answer questions during the course.


    • 25 Aug 2020
    • 11:00 AM - 12:30 PM (UTC+10:00)
    • Online
    Register

    The past two decades have seen a phenomenal change in the landscape of statistical analysis. Datasets are now available that are of unprecedented volume, complexity in structure, and are coming from designs and sources that present new and exciting challenges.

    What are the challenges in statistical consulting and how are they impacted by this changing landscape? What are the consulting and communication skills needed to support successful consultation? And what has been the impact of the COVID-19 pandemic?

    We bring together four statistical consultants with vast collective experience to share their insights with us. Eminent international statistical consultant, Professor Doug Zahn, invites you to send your stumbling blocks in communication for discussion. Each speaker will present a short talk, followed by a panel discussion.

    This event will be held online and is for members of SSA and NZSA only. Membership with NZSA will be confirmed with NZSA.

    Please register to receive the link to join the event.

    This event is hosted jointly by the Statistical Consulting Network, the Canberra Branch and the Victorian Branch.

    Speakers

    Moderator: Alice Richardson, Australian National University

    Details of each talk:

    An abundance of data

    Data is plentiful in the 21st century and with it comes a range of new opportunities and challenges. Whether data has been manually entered or automated, consideration needs to be given to the accuracy and fit for the questions at hand to make meaningful interpretations. Understanding data quality can be especially challenging with increasingly large and complex datasets and time constraints in a business environment. I will share examples of challenges faced and lessons learned from her wealth of experience.


    Elyse Corless is a Senior Consultant Statistician at Data Analysis Australia experienced in the areas of applied statistics, surveys, sampling, mapping and forecasting. Examples of the diverse range of projects she has contributed to include community surveys relating to legal applications, forecasting for courts and utility providers and financial assurance activities.

    Statistical consulting: the art of the possible

    In my 3.8 decades of statistical consulting, I have found that good consulting requires attention to quality in several areas simultaneously – these include technical and personal skills, clarity of explanation (verbal and written), organisation, lavish communication, and judgment as to what is needed and what the client can handle. Any of these, if neglected, can mess up a consulting project, but the last aspect is not usually given much attention.

    Having spent equal time consulting in the 20th and 21st centuries (P = 0.87 on a sign test), with the latter obviously affording more new opportunities, I have found that “the art of the possible” is still a useful guiding motivation. While the sky’s the limit (and occasionally is achieved), an early assessment of what is realistically achievable results in a better outcome for the client and less pain for the consultant.


    Graham Hepworth has worked as a statistical consultant for as long as he can remember – well, almost. After trying his hand as a mathematics teacher, he moved into consulting – at the ABS (2 yrs), in forestry research (5 yrs), agricultural research (11 yrs), and now general consulting (20 yrs and counting – close to a geometric sequence). He has consulted and collaborated in most broad areas of research and investigation, and he particularly enjoys the design and analysis of experiments, and sampling problems.

    Statistical consulting in the university: some challenges

    Statistical consulting in a university context typically involves a collaboration between a statistician and a researcher, with the aim to devise solutions to research problems involving data. The researcher comes with domain expertise in the sciences or social sciences, and the statistician brings their expertise in experimental/survey design and data analysis. A successful collaboration is a complex activity that requires more from the statistician than statistical knowledge. As statistical consultants, we help researchers to understand the statistical framework of their problem so that researchers themselves can take appropriate action and develop greater statistical competence in the process. Our ability to interact empathetically with our clients determine the ultimate success of the consultation.

    This presentation focuses on some (general) challenges associated with statistical consulting at universities, which I will illustrate with stories from my 12 years as a consultant at ANU.


    Hwan-Jin Yoon joined the Statistical Consulting Unit at The Australian National University in 2008, having previously worked in the Department of Primary Industries in Victoria as a biometrician. He completed his PhD in applied statistics at the University of Melbourne, 2005. He has extensive experience in experimental design, random effects models, statistical moderation, survival analysis, and multivariate analysis in social science, medical science, environmental science, ecology, biology and engineering and computer science.
    Hwan-Jin Yoon is an Accredited Statistician (AStat) with the Statistical Society of Australia.

    What is your most troublesome stumbling block?

    In my experience, we share stumbling blocks. The most effective way of addressing them is in open conversations with colleagues with similar concerns. Please submit a description of your stumbling blocks when you register for this event. We will collate and anonymise them, and explore the most frequent ones in our time together. (Thank you in advance for your commitment of time and energy to our time together.)


    Doug Zahn earned a doctorate in statistics from Harvard University. He is a professor emeritus of the Florida State University department of statistics, where he taught applied statistics and statistical consulting courses for 35 years. He provided consulting services to faculty and students. For over nine years he coached consulting professionals at the United Kingdom Office for National Statistics while co-teaching a course on consultancy skills. Doug is the co-author of The Human Side of Statistical Consulting and Quality Management Plus: The Continuous Improvement of Education. He and his wife, Andrea, live in Tallahassee, Florida.

    Doug most recently published Stumbling Blocks to Stepping Stones: A Guide to Successful Meetings and Working Relationships (2019). In this book he discusses how to improve your conversations, thereby building more effective relationships, whether with friends or those you perceive as adversaries.

    • 31 Aug 2020
    • 9:00 AM (UTC+10:00)
    • 4 Sep 2020
    • 12:30 PM (UTC+10:00)
    • Online

     Introduction to Regression Modelling in R

    Course Overview

    The core outcome from this course is to recognise that most statistical methods you use can be understood under a single framework, as special cases of (generalised) linear models. Learning statistical methods in a systematic way, instead of as a "cookbook" of different methods, enables you to take a systematic approach to key steps in analysis (like assumption checking) and to extend your skills to handle more complex situations you might encounter in the future (random factors, multivariate analysis, choosing between a set of competing models). 

    This short course, taking place over five half-days, is aimed at applied researchers with prior experience using R and familiar with introductory statistics tools - you should know about the t-test, linear regression, analysis of variance and know something about orthogonal and nested designs. If you have not used R before, we strongly recommend you learn basic features of R and how to use the RStudio interface to R before this course. If you have no experience with R, Stats Central offers an Introduction to R short course, which will be run on 11-12 August and 19-20 August (see above). If you need to revise introductory statistics material, you should attend the Introductory Statistics for Researchers course on 24-27 August (see above), as the material in it is taken as assumed knowledge for this regression course. 

    Course Requirements

    You will need to use a computer during the course. Some familiarity with introductory statistics and R will be assumed. 

    Date:               Monday 31 August to Friday 4 September, 2020 (five morning sessions)

    Duration:         9.00 am to 12.30 pm – Each day

    Location:         Online

    For further details and bookings:

    https://www.eventbrite.com.au/e/online-short-course-introduction-to-regression-modelling-in-r-tickets-112570338914

    Stats Central provides study design and analysis support to all UNSW researchers, in collaborative and consultative roles, and conducts short courses and monthly seminars on topical issues. Please see below for our upcoming seminar and short courses. Please feel free to circulate this email to your colleagues, staff, researchers and students, who may be interested. Should you have any questions please don’t hesitate to contact us or visit our website statscentral.unsw.edu.au.

    **Due to the COVID-19 situation, we are offering online course with 20% discounted rates.**

    Note: The courses will be delivered remotely using online collaborative teaching tools, with a mix of live video-assisted lectures and computer-based tutorials. A continuous chat session will be available and there will be extra staff to answer questions during the course.


    • 1 Sep 2020
    • 10:00 AM (UTC+10:00)
    • 2 Sep 2020
    • 1:00 PM (UTC+10:00)
    • Online

    Introduction to Python for Data Science

    Course Overview

    Python is a widely used programming language to manipulate, analyze, and visualize data. It is one of the most popular languages for Data Science, especially when dealing with complex, uncurated or text datasets. 

    This course assumes that you have never used Python before, but you have some basic programming knowledge. You will learn how to obtain and install Python, which is open-source software, and Jupyter Notebook, which is an interactive computational environment, in which you can combine code execution, rich text, mathematics, plots and rich media. 

    This two half-days introduction to Python will cover some useful features of Python for data science. It will discuss various online resources available to further develop your data science skills using Python.

    Presenter: A/Professor Raymond Wong (Stats Central and UNSW School of Computer Science and Engineering)

    Course Requirements: You will need a computer.

    Date:               Tuesday 1 & Wednesday 2 September, 2020 (two half-day sessions)

    Duration:         10.00 am to 1.00 pm – Each day

    Location:         Online

    For further details and bookings:

    https://www.eventbrite.com.au/e/online-short-course-introduction-to-python-for-data-science-tickets-112899814384

    Stats Central provides study design and analysis support to all UNSW researchers, in collaborative and consultative roles, and conducts short courses and monthly seminars on topical issues. Please see below for our upcoming seminar and short courses. Please feel free to circulate this email to your colleagues, staff, researchers and students, who may be interested. Should you have any questions please don’t hesitate to contact us or visit our website statscentral.unsw.edu.au.

    **Due to the COVID-19 situation, we are offering online course with 20% discounted rates.**

    Note: The courses will be delivered remotely using online collaborative teaching tools, with a mix of live video-assisted lectures and computer-based tutorials. A continuous chat session will be available and there will be extra staff to answer questions during the course.


    • 3 Sep 2020
    • 6:00 PM - 7:00 PM (UTC+09:30)
    • virtual Zoom meeting

    Branch Meeting - Thursday, 3rd September 2020

    The South Australian Branch of the Statistical Society would like to invite you to one of two September meetings of the 2020 program.

    Virtual Venue via Zoom meeting. The meeting link will be published shortly.

    Speaker: Dr Margherita Silan, Padua University

    Topic: Propensity score techniques in multiple treatment framework: the estimation of neighbourhood effect

    Abstract

    The study of neighbourhood effects on health conditions has gained attention exponentially during last decades. This topic is even more important from a public health perspective when the focus is on health conditions of elderly, whom spend more time in their neighbourhood than young people. The study estimates neighbourhood effects on elderly health outcomes in Turin (a city located in north Italy) using data coming from the Turin Longitudinal Study, that contains linked individual data from censuses and administrative health data flows. Individuals are not randomly distributed among neighbourhoods, the residential area is chosen also on the basis of individual socio-economic characteristics. This causes a selection bias, that may confound comparisons between the distribution of health outcomes among neighbourhoods. In order to balance observable confounders and to make different populations living in different neighbourhoods comparable, we adopted a propensity score approach. The original methodological contribution of our work is the adaptation of propensity score techniques to a framework with many treatments (that are neighbourhoods in this application). Indeed, Turin may be divided according to three geographical partitions in 10, 23 or 94 neighbourhoods. We proposed a novel method that consists on a Matching on Poset based Average Rank for Multiple Treatments (MARMoT), which has revealed to be really useful to improve the covariates’ balance between groups and pretty fast with respect to other approaches, that have revealed to be unpractical in applications with many treatments.

    Biography

    Margherita Silan is a postdoctoral research fellow at the Department of Statistical Sciences, Padua University. She received a PhD degree from the Padua University, in 2019. Margherita is also the winner of the Italian Statistical Society annual award for best PhD in Applied Statistics. Her research interests include causal inference in multiple treatment frameworks, composite indicators and partially ordered set theory. The application areas are public health, ageing and gender equality.

    Feel free to forward this meeting notice to colleagues, all welcome.


    • 8 Sep 2020
    • 10:00 AM (UTC+10:00)
    • 9 Sep 2020
    • 1:00 PM (UTC+10:00)
    • Online

    Text Analytics in Python (Advanced)

    Course Overview

    More than 70% of the data on the internet is unstructured. Among them, text is the most common form that appears in almost all data sources. For example, text data such as emails, online reviews, tweets, news and reports hold valuable information and insight for most research and applications. Text analytics, usually involving techniques from text mining or natural language processing (NLP), can automatically uncover patterns and extract meaning/context from these unstructured texts. 

    This course assumes that you have basic Python programming knowledge, or have previously attended "Introduction to Python for Data Science" from Stats Central. This course will provide you the foundation to process and analyze text. 

    In this course, we will cover some useful Python features and libraries for text processing and analysis. We will touch on some advanced topics such as sentiment analysis, text classification, and/or topic extraction. 

    Presenter: A/Professor Raymond Wong (Stats Central and UNSW School of Computer Science and Engineering)

    Course Requirements: You will need a computer.

    Date:               Tuesday 8 & Wednesday 9 September, 2020 (two half-day sessions)

    Duration:         10.00 am to 1.00 pm – Each day

    Location:         Online

    For further details and bookings:

    https://www.eventbrite.com.au/e/online-short-course-text-analytics-in-python-advanced-tickets-112901224602

    Stats Central provides study design and analysis support to all UNSW researchers, in collaborative and consultative roles, and conducts short courses and monthly seminars on topical issues. Please see below for our upcoming seminar and short courses. Please feel free to circulate this email to your colleagues, staff, researchers and students, who may be interested. Should you have any questions please don’t hesitate to contact us or visit our website statscentral.unsw.edu.au.

    **Due to the COVID-19 situation, we are offering online course with 20% discounted rates.**

    Note: The courses will be delivered remotely using online collaborative teaching tools, with a mix of live video-assisted lectures and computer-based tutorials. A continuous chat session will be available and there will be extra staff to answer questions during the course.


    • 25 Sep 2020
    • 12:00 PM - 1:00 PM (UTC+10:00)
    • via Zoom
    • 287
    Register

    You are warmly invited to the following webinar hosted by SSA:

    Random Effects Inference in Linear Mixed Models: The good, the bad, and the misspecified

    held on Friday, 25 September 2020 at 12:00PM AEST via Zoom, exclusively for members of SSA.

    This event is presented by Francis K.C. Hui and Alan H. Welsh (Research School of Finance, Actuarial Studies & Statistics, Australian National University).

    About this webinar:

    In many applications of mixed models, the scientific questions of interest can often relate to estimation and inference of the random effects . Examples range from assessing the importance of all or a subset of the variance components, constructing functions and associated uncertainty intervals of functions of the random effects and/or variance components, to directly modelling the random effects as a function of other covariates. On the other hand, unlike fixed effects inference there is a lot more contention and uncertainty (pun intended!) surrounding both how to do random effects inference in mixed models, and what the consequences are of associated misspecification on estimation and inference.

    This talk is a culmination of two projects on the topic of random effects inference in linear mixed models. In the first half, we re-examine one of the earliest and simplest methods of random effects testing in linear mixed models, namely the F-test based on linear combinations of the responses, or FLC test. For current statistical practice, we argue that the FLC test is underused and should be given more consideration especially as an initial or “gateway” test for linear mixed models. We discuss three advantages of the FLC test often overlooked in modern applications of linear mixed models: computation speed, generality, and its exactness as a test. In the second half, we examine some impacts of random effects misspecification on random effects inference in linear mixed models. While some large sample results can be formulated, we show that in general that incorrectly assuming a normal distribution for the random effects can have severe consequences for random effects inference, with strongly biased estimation of variance components and associated likelihood-based confidence intervals for the variance components exhibited potentially severe under coverage.

    If time permits, we conclude our talk by encouraging more general discussion and research on the notion of sometimes treating random effects as fixed effects for estimation and inference, and how the above findings may generalise far beyond linear mixed models.

    About the presenters:

    Francis K.C. Hui and Alan H. Welsh (Research School of Finance, Actuarial Studies & Statistics, Australian National University)

    Francis Hui is a Senior Lecturer in Statistics at the Australian National University. He completed his PhD at the University of New South Wales in 2014 and moved to Canberra to undertake a postdoctoral fellowship at the ANU, and has been willingly stuck there since. His research spans a mixture of methodological, computational, and applied statistics, including longitudinal and correlated data analysis, dimension reduction and variable selection, and approximate statistical estimation and inference. Much of his research is motivated by joint modelling in ecology, and longitudinal analysis of mental health data, and is complemented by copious amounts of tea drinking, and unhealthy amounts of anime watching.

    Alan Welsh, recipient of the Pitman Medal in 2012, is the E.J. Hannan Professor of Statistics at the Australian National University. He has been at ANU for a while, spending time in the Mathematical Sciences Institute and the Research School of Finance, Actuarial Studies & Statistics. He has also held positions at the University of Chicago and the University of Southampton. His research interests include statistical inference, statistical modelling, robustness, nonparametric and semiparametric methods, analysis of sample surveys, and ecological monitoring. Much of his recent work has gone into trying to understand linear mixed models better.

    Registration

    This event is for members of SSA and members of NZSA. (If you register as a member of NZSA please note that we will confirm your membership with our colleagues of the NZSA). The event is free, but you will need to register. Registration is a 2-step process. Please use the registration link on the left to register with SSA. You will receive a confirmation email containing a link for the registration with Zoom.  Please complete the registration with Zoom at your earliest convenience as places on our Zoom platform are limited!

    This event will be recorded and the recording added to SSA’s webinar page in due course after the event.

    Would you please note that the times stated are AEST?

    Cancellation Policy

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    Our goal is to provide truly exceptional offerings and service, and we won't be happy until you are. If any programs, products or services of SSA do not fulfill our promise, we will make the situation right.

    Event Cancellation or Postponement
    SSA reserves exclusive right to modify, postpone/reschedule or cancel programs for any reason, including but not limited to emergency, inclement weather or other 'acts of God'. If there is an event cancellation, every attempt will be made to reschedule, and registration fees will be applied to the rescheduled event date. Any travel, lodging, or incidental expenses incurred related to a cancelled event cannot be refunded under any circumstances. 

    Consent to Use of Photographic Images
    Registration and attendance at, or participation in, SSA meetings and other activities constitutes an agreement by the registrant to the use and distribution of the registrant or attendees' image or voice in photographs, videotapes, electronic reproductions and audiotapes of such events and activities by SSA. 

    If you have any questions, please contact Marie-Louise Rankin, SSA Executive Officer.


    • 28 Sep 2020
    • (UTC+02:00)
    • 29 Sep 2020
    • (UTC+02:00)
    • Strasbourg, France

     The Centennial of the International Mathematical Union

    As you may know, the IMU was founded in September 1920 in Strasbourg, France. On  the occasion of the centennial of the IMU, we are organizing the conference               

     Mathematics without Borders
    The Centennial of the International Mathematical Union
                 

    You are cordially invited to participate in this conference. We will get back

    with further information regarding registration, accommodation, etc as

    soon as it is available. 

     


    • 30 Sep 2020
    • (UTC+08:00)
    • 1 Oct 2020
    • (UTC+08:00)
    • 2 sessions
    • Perth

    UPDATE: We are currently exploring the format and pricing of this meeting due to the COVID-19 situation. Registration is therefore temporarily disabled.

    Don’t miss out on your chance to meet other young statisticians and leading members of WA’s statistical and data science community. Speakers from industry and academia.

    Young Statisticians are invited to submit an abstract to present a short talk or poster on your research with statistics to win prizes! Please send your queries to ysmurdoch@gmail.com

    • 30 Sep 2020
    • 11:00 AM (UTC+10:00)
    • 2 Oct 2020
    • 1:00 PM (UTC+10:00)
    • via Zoom
    • 22
    Register

    Please join us for the following online workshop

    Semiparametric Regression with R

    to be held over three days:

    11:00am-1:00pm (Australian Eastern Standard Time) Wednesday 30th September 2020

    11:00am-1:00pm (Australian Eastern Standard Time) Thursday 1st October 2020

    11:00am-1:00pm (Australian Eastern Standard Time) Friday 2nd October 2020

    About the presenter

    Matt P. Wand is a Distinguished Professor of Statistics at the University of Technology Sydney. He has held faculty appointments at Harvard University, Rice University, Texas A&M University, the University of New South Wales and the University of Wollongong. Professor Wand is an elected fellow of the Australian Academy of Science, the American Statistical Association and the Institute of Mathematical Statistics. He was awarded two of the Australian Academy of Science's medals for statistical research: the Moran Medal in 1997 and the Hannan Medal in 2013. In 2014 he was awarded the Statistical Society of Australia's Pitman Medal. He has served as an associate editor for several journals including Biometrika, Journal of the American Statistical Association and Statistica Sinica. He has co-authored 2 books, more than 120 journal articles and 6 R packages on semiparametric regression and related areas.

    Further details about Professor Wand’s research, and every paper he has written, are on the website.


    About the course

    Semiparametric regression methods build on parametric regression models by allowing more flexible relationships between the predictors and the response variables. Examples of semiparametric regression include generalized additive models, additive mixed models and spatial smoothing. The presenter's goal is to provide an easy-to-follow applied course on semiparametric regression methods using R. There is a vast literature on the semiparametric regression methods. However, most of it is geared towards researchers with advanced knowledge of statistical methods. This course is intended for applied statistical analysts who have some familiarity with R.

    This short course explains the techniques and benefits of semiparametric regression in a concise and modular fashion. Spline functions, linear mixed models and Bayesian hierarchical models are shown to play an important role in semiparametric regression. There will be a strong emphasis on implementation in R and rstan with most of the short-course spent doing computing exercises.

    The workshop is based on the in-press book “Semiparametric Regression with R” by  J. Harezlak, D. Ruppert and M.P. Wand (Springer, 2018), with website http://semiparametric-regression-with-r.net/, and has the companion methodology and theory book “Semiparametric Regression” by D. Ruppert, M.P. Wand and R.J. Carroll (Cambridge University Press, 2003), with website.

    Target Audience

    Most of the course will be geared towards researchers with intermediate to advanced knowledge of statistical, particularly regression, methods.

    Learning Objectives

    1. Introduction to semiparametric regression at the applied level

    2. Implementation of the presented methods in R and rstan

    3. Application of the newly learned methods to a variety of datasets


    Fees

    Early Bird rates (Registration and payment before 1 September)

    Early Bird SSA Members

    $150

    Early Bird Non-Members

    $390

    Early Bird Students

    $100

    Early Bird Non-Member Students

    $130


    Rates from 1 September 

    SSA Members

    $200

    Non-Members

    $440

    SSA Student Members

    $150

    Non Member Students

    $180


    Cancellation Policy

    Cancellations received prior to Wednesday, 23 September 2020 will be refunded, minus a $25 administration fee.

    From then onwards no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to eo@statsoc.org.au.

    Our Guarantee

    Our goal is to provide truly exceptional offerings and service, and we won't be happy until you are. If any programs, products or services of SSA do not fulfill our promise, we will make the situation right.

    Event Cancellation or Postponement

    SSA reserves exclusive right to modify, postpone/reschedule or cancel programs for any reason, including but not limited to emergency, inclement weather or other 'acts of God'. If there is an event cancellation, every attempt will be made to reschedule, and registration fees will be applied to the rescheduled event date. Any travel, lodging, or incidental expenses incurred related to a cancelled event cannot be refunded under any circumstances. 

    Consent to Use of Photographic Images

    Registration and attendance at, or participation in, SSA meetings and other activities constitutes an agreement by the registrant to the use and distribution of the registrant or attendees' image or voice in photographs, videotapes, electronic reproductions and audiotapes of such events and activities by SSA. 

    • 11 Nov 2020
    • (UTC+11:00)
    • 12 Nov 2020
    • (UTC+11:00)
    • 2 sessions
    • Online
    • 19
    Register

    Statistical Society of Australia warmly invites you to a workshop on data visualisation with R, taught by Prof. Di Cook and Dr. Emi Tanaka.

    This is a repeat of the July workshop. Please note there may be slight changes based on past participant feedback.

    About the workshop:

    Data visualisation is a key statistical tool for effective communication and to understand aspects of data and models. The statistical language R is used widely for data analysis and visualization, e.g. the BBC Visual and Data Journalism team uses ggplot2 R-package to create production-ready charts. This workshop (on Day 1) will teach you how to create production-ready graphics using the grammar of graphics implemented in ggplot2 R-package. In addition, the workshop (on Day 2) will teach you how to construct more complex plots, including maps, and discuss inference for statistical graphics to understand if what we see in a plot is really there. The workshop will be hands-on with plenty of practical examples.

    About the presenters:

    Dianne Cook is Professor of Business Analytics at Monash University in Melbourne, Australia.  She is a world leader in data visualisation, especially the visualisation of high-dimensional data using tours with low-dimensional projections, and projection pursuit.  She is currently focussing on bridging the gap between exploratory graphics and statistical inference.  Di is a Fellow of the American Statistical Association, past editor of the Journal of Computational and Graphical Statistics, current editor of the R Journal,  elected Ordinary Member of the R Foundation, and elected member of the International Statistical Institute. 

    Emi Tanaka is a Lecturer in Statistics at Monash University and the Vice President of SSA Vic. She is currently working on a statistical theory for conducting inference using data plots and is an early career researcher in multi-level modelling, and experimental design. She is an experienced and enthusiastic R user and instructor, and regularly teaches university courses and workshops to the broader community on data visualisation, including ggplot2.

    Target audience:

    Day 1 is suitable for those who know R but are not familiar or comfortable with using ggplot2 or would like a refresher on ggplot2. 

    Day 2 is aimed for those that have familiarity with ggplot2 but would like to delve deeper into advanced plotting techniques, including interactive plots and animating plots, and using plots for inference. 

    Learning objectives:

    Day 1: Dipping Your Toes into Data Visualization with R

    Presented by Emi Tanaka

    • Review of tidy data format

    • Basics of the grammar of graphics

    • Drawing the basic data plot types (barchart, pie chart, histogram, density plot, scatterplot, boxplot) utilising a range of common geoms and variable mappings

    • Choosing colour wisely

    • All about scales, transforming data, setting limits, changing coordinate systems, axis specifications, ordering levels of categorical axes

    • Jazzing up your plot with different themes, plot annotations and combining plots together to make a publication-ready plot

    Day 2: Diving Deeper into Data Visualization with R

    Presented by Di Cook

    • Check your knowledge, a review of basic plotting with the grammar

    • Expanding your graphics toolbox to mapping, making choropleth maps, using map images as a base

    • Making your plots speak. Adding interactive elements including mouse-over labels, and sliders for controlling parameters, using plotly. Animating plots using gganimate.

    • Learn how to decide on the best plot design for a problem, and how to  determine if what you see is a real structure.  

    Requirements:

    Day 1

    • basic R knowledge (e.g. you have used R to load data, create simple visualisations, perform basic analyses and write simple functions or more specifically, you are familiar with concepts in Cookbook for R by Winston Chang)

    • basic statistics (e.g. simple linear regression, hypothesis testing, basic summary statistics and plots)

    • computer (with ability to install R and R-packages), microphone and web camera 

    • stable internet connection

    • Install the video conferencing software, zoom and know how to use zoom

    Day 2:

    • Day 1 requirements

    • Completed Day 1 OR know basic ggplot2

    Desirable:

    • Know about tidy data (i.e. importing data and putting data into the right format for plotting)

    • Some familiarity with tidyverse

    Timetable

    Please note that we may modify the schedule slightly after feedback from our July workshop.

    Day 1

    1:30pm  3.00pm (1.5 hours)

    Session 1

    3.00pm  3.30pm

    Break / networking over virtual morning tea

    3.30pm  5:00pm (1.5 hours)

    Session 2

    12:30pm

    End of first day

    Day 2

    1.30pm  3.00pm (1.5 hours)

    Session 1

    3.00pm 3:30pm

    Break / networking over virtual morning tea

    3:30pm  5:00pm (1.5 hours)

    Session 2

    5:00pm

    End workshop


    Deadlines: Early Bird registration closes on
     22 Sep 2020. Regular registrations close on midnight on 3 Nov 2020.

    Expenses:

    Occasionally workshops have to be cancelled due to a lack of subscription. Early registration ensures that this will not happen. Please note that the Society will not be held responsible for any financial loss incurred due to a workshop cancellation.

    Financial Support:

    Financial support for SSA Vic members can be sought. For further information, please see: https://sites.google.com/view/ssavicworkshopfinsup.

    Cancellation policy:

    Cancellations received prior to 20 Oct 2020 will be refunded, minus a $20 administration fee. From then onwards no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to eo@statsoc.org.au..

    Contact:

    Please contact the organisers: Rheanna Mainzer (rheanna.mainzer@gmail.com), Lidija Turkovic (lidijat@gmail.com), and Emi Tanaka (dr.emi.tanaka@gmail.com) for further details.

    • 24 Nov 2020
    • 12:30 PM - 2:00 PM (UTC+11:00)
    • Online

    SSA Canberra invites you to attend this year's Knibbs lecture, which will be presented by Prof. Ray Carroll (Texax A&M). The lecture will also celebrate the 60th birthday of Prof. Alan Welsh (ANU), and his contributions to statistics. 


    Date:  Tuesday 24th November

    Time: 12:30pm-1:45pm AEST.  

    More details will be announced closer to the date of the event, including registration to attend the Zoom meeting.


    • 2 Dec 2020
    • (UTC+11:00)
    • 4 Dec 2020
    • (UTC+11:00)
    • Sydney, Australia

    The Australian Consortium of Social and Political Research Incorporated (ACSPRI) will host it's 7th Social Science Methodology Conference on the 2nd to 4th of December at The University of Sydney.

    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 two 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).

    More details will appear on the conference website soon. 

    • 5 Jul 2021
    • 8:00 AM (UTC+10:00)
    • 9 Jul 2021
    • 6:00 PM (UTC+10:00)
    • Gold Coast Convention Centre, 2684 -2690 Gold Coast Highway, Broadbeach, QLD

    Welcome to the 
    ANZSC 2021 Conference

    The organising committee warmly invites you to the 2021 Australian and New Zealand Statistical Conference, which will take place on the Gold Coast from the 5th to the 9th of July 2021.

    This conference brings together four leading statistical communities in the region – the Statistical Society of Australia, the New Zealand Statistical Association, the International Institute of Business Analysis (Special Interest Group for Business Analytics), and the Australian Conference on Teaching Statistics.

    The aim of this conference is to bring together a broad range of researchers and practitioners across a variety of statistical disciplines to facilitate the exchange of theory, methods and applications.

    With these four societies working together there will be strong program components of interest to a wide diversity of academic, government, and industry colleagues. This includes the full spectrum of delegates from those advancing theoretical methodology to those working on industry applications (in traditional and non-traditional statistical areas). Of particular interest is how Big Data continues to impact all of us.

    Information on Keynote Speakers and the Conference program will be available shortly so watch this space for updates.

    The conference will be held at the Gold Coast Convention and Exhibition Centre (GCCEC) situated in the heart of the Gold Coast. From GCCEC, Surfers Paradise (the social hub of the Gold Coast) is 5km to the North, the Star Casino and Pacific Fair are immediately to the South (the largest regional shopping and dining destination in Queensland), the beach (Broadbeach) is just ten minutes walk, and the Broadbeach restaurant complex is immediately to the East (short 5 minutes walk). Social tours can easily be made to the rainforest (such as Tambourine National Park and World Heritage-listed Lamington National Park), to places of Aboriginal Indigenous significance, to Stradbroke Island, and to Australia’s greatest theme parks.

    ANZSC2021 promises to be a truly amazing experience on both a professional and a social level.

    Please check out the official conference website and register your interest here.

    We look forward to seeing you on the Gold Coast in 2021!

    • 11 Jul 2021
    • (UTC+10:00)
    • 15 Jul 2021
    • (UTC+10:00)
    • The Hague, The Netherlands

    The 63rd ISI World Statistics Congress will bring together statisticians and data scientists from academia, official statistics, health sector and business, junior and senior professionals, in an inviting environment.

    The inspiring and interactive programme will provide the platform to learn about the latest developments in statistical research and practice in an informal ambiance. A series of short courses, satellites and other events completes the WSC programme.

    • 27 Sep 2021
    • (UTC+10:00)
    • 28 Sep 2021
    • (UTC+10:00)
    • Strasbourg, France

    Mathematics without Borders

    The Centennial of the International Mathematical Union         

    celebrates the centennial of this historic event.  Up-to-date information regarding the conference can be found here




    • 27 Jun 2022
    • (UTC+10:00)
    • 1 Jul 2022
    • (UTC+10:00)
    • Darwin, Australia

    The inaugural

    Joint Southern Statistical Meetings 2022

    will be held in Darwin from 27 June – 1 July 2022.

    This conference will bring together the leading statistical communities in the region to provide a forum for researchers and practitioners across a variety of statistical disciplines to facilitate the exchange of theory, methods and applications.

    To be kept up to date with our conference planning, please email your details to JSSM2022@gmail.com.

    We invite regional associations to contact us with expressions of interest to be part of this event. If you would like to sponsor JSSM2022 please get in touch as well.

    See you in Darwin in 2022! 

    • 6 Jul 2022
    • (UTC+10:00)
    • 14 Jul 2022
    • (UTC+10:00)
    • St Petersburg, Russia

    The ICM 2022 (International Congress of Mathematicians) will take place 6–14 July 2022 in St. Petersburg, Russia.

    The 19th General Assembly of the IMU will be held in St. Petersburg, on 3–4 July 2022. 
    The official website of the Congress is https://icm2022.org

    • 10 Jul 2022
    • (UTC+10:00)
    • 15 Jul 2022
    • (UTC+10:00)
    • Riga, Latvia

    to be held at the Radisson Blu Latvija Conference & Spa Hotel


Past events

14 Aug 2020 SA Branch Young Statisticians Career Event
11 Aug 2020 WA joint seminar with IBS - Dr Smaila Sanni
11 Aug 2020 External event: Introduction to R
6 Aug 2020 P-Values and "Statistical Significance": Deconstructing the Arguments
4 Aug 2020 SSA and ASPAI AGMs
31 Jul 2020 Talking to stakeholders: Statistics in the outside world
28 Jul 2020 Sharpening the BLADE - Missing Data Imputation using Supervised Machine Learning
28 Jul 2020 Workshop: Data visualisation with R
24 Jul 2020 SSA Webinar: Writing successful fellowships
24 Jul 2020 Workshop: Introduction to Julia for Statistics and Data Science
21 Jul 2020 'The Eye of the Beholder' : Regression Coefficients & Mechanical Objectivity in Public Health Research
20 Jul 2020 Workshop: Machine learning with Python
19 Jul 2020 The 35th International Workshop on Statistical Modelling (IWSM2020)
15 Jul 2020 SA Branch webinar - Dr Natalie Twine
10 Jul 2020 Games Night - Plan your escape from our virtual Escape Room
10 Jul 2020 Virtual Poster Pitch
9 Jul 2020 SSA+NZSA virtual mini-conference
1 Jul 2020 Workshop of the 20th International Conference on Computational Science and Applications
30 Jun 2020 Beyond Beamer: Joint SSA Canberra/NSW + RLadies Meeting
26 Jun 2020 SSA Course: P-values and the normal assumption in scientific research.
23 Jun 2020 SSA Vic Mentoring Evening
22 Jun 2020 7th International Statistical Ecology Conference- external event
19 Jun 2020 Webinar: Getting to know our “cell mates”: A practical approach to microbiome analysis through a biostatistician’s lens.
17 Jun 2020 SA Branch webinar - Dr Oscar Perez-Concha
16 Jun 2020 Queensland branch meeting: Leveraging statistical shapes in genomics, looking beyond what’s Normal
10 Jun 2020 Webinar: Inquiry into the performance of the opinion polls at the 2019 Australian Federal Election – Update of progress made by the enquiry
9 Jun 2020 WA branch seminar - Dr Brenton R Clarke
5 Jun 2020 Seminar: Inferring genetic linkage maps from high-throughput sequencing data
2 Jun 2020 Queensland Branch meeting: "MIGHTY MAPS: Showcasing estimate uncertainty"
28 May 2020 Virtual Coffee - Member Catch Up and Discussion
27 May 2020 Webinar: A short overview into “how to make a learning healthcare system work”: from linking data, machine learning to ethics
27 May 2020 Queensland Branch Meeting: Searching for dark matter and new physics with GAMBIT
26 May 2020 Raising Heretics: Teaching effective scepticism using data science
21 May 2020 Data Collection in a time of multiple crises: The social research response to COVID-19, bushfires, and drought
19 May 2020 Trivia Night via Zoom, hosted by SSA Victoria
19 May 2020 Short Course: Study Design
12 May 2020 WA Young Statisticians Meeting
12 May 2020 Short Course: Introductory Statistics for Researchers
8 May 2020 SSA seminar: Jim Thorson (NOAA), Forecasting nonlocal climate impacts for mobile marine species using extensions to empirical orthogonal function analysis
4 May 2020 Short Course: Introduction to R
30 Apr 2020 Virtual Coffee - Member Catch Up and Discussion
28 Apr 2020 Vic Branch – COVID-19: modelling and public health policy
22 Apr 2020 SA Branch Meeting - Dr Murthy Mittinty
16 Apr 2020 Webinar: Learning about Covid-19 Known Unknowns: the essential role of statisticians
14 Apr 2020 WA Branch Meeting - Assoc/Prof Rachel Cardell-Oliver
31 Mar 2020 Vic Branch – Measuring Well-being
31 Mar 2020 SSA Vic AGM
26 Mar 2020 NSW Branch: AGM + Lancaster Lecture
25 Mar 2020 SA Branch Annual General Meeting
20 Mar 2020 SSA Webinar: Tales of an Applied Statistician
10 Mar 2020 WA Branch AGM and Meeting - Mark S. Handcock
5 Mar 2020 Bayesian Adaptive Randomised Clinical Trials Workshop
3 Mar 2020 Queensland Branch AGM 2020
27 Feb 2020 Bayesian Adaptive Randomised Clinical Trials Workshop
21 Feb 2020 Webinar: Statistical Machine Learning for Spatio-Temporal Forecasting
19 Feb 2020 SA Branch Meeting - Prof Omer Ozturk
7 Feb 2020 SSA Webinar: Do we die of only one cause?
11 Dec 2019 rOpenSci OzUnconf 2019 - external event
10 Dec 2019 Vic Branch – We all count: Strengthening stats and maths through diversity
9 Dec 2019 UQ Institute for Social Science Research: Longitudinal Data Analysis Course
6 Dec 2019 E. A. Cornish Memorial Lecture - SA Branch Meeting
6 Dec 2019 South Australia Biostatistics Networking
6 Dec 2019 SA Cornish Lecture
4 Dec 2019 UNSW Biostatistics Seminar
4 Dec 2019 Bayesian adaptive trials workshop - external event
3 Dec 2019 Webinar: Communicating risk and uncertainty with Sir David Spiegelhalter
3 Dec 2019 Queensland branch Xmas event
3 Dec 2019 Introduction to Python for Data Science - external event
3 Dec 2019 Biometrics by the Botanic Gardens 2019 - external event
2 Dec 2019 17th Australasian Data Mining Conference (AusDM’19) - external event
1 Dec 2019 Workshops at Biometrics by the Botanic Gardens 2019 - external event
29 Nov 2019 Data Science and Social Good Symposium - external event
28 Nov 2019 WOMBAT 2019
26 Nov 2019 WA Branch: End of year dinner
26 Nov 2019 Sample Size and Power Calculations - external event
26 Nov 2019 UQ Institute for Social Science Research: Social Cost-Benefit Analysis Course - external event
25 Nov 2019 CPD95 - Bayes on the Beach 2019
21 Nov 2019 Workshop: Pragmatic randomised trial designs for evaluating health policy and practice change interventions - external event
19 Nov 2019 CPD108 - R skills workshops: Building R packages and R Markdown
19 Nov 2019 UQ Institute for Social Science Research: Gathering Qualitative Data Course - external event
19 Nov 2019 Bayesian Logistic Regression in Practice, using R or Autostat - External Event
18 Nov 2019 Webinar: Modelling Molecule Dropout in single cell RNA-seq Experiment Leads to Improved Identification of Marker Genes
18 Nov 2019 CPD107 - Machine Learning with Python
13 Nov 2019 NSW Branch: Annual Dinner
13 Nov 2019 NSW Branch: Annual Lecture by Prof Ian Marschner
13 Nov 2019 NSW Branch: J. B. Douglas Awards
13 Nov 2019 UQ Institute for Social Science Research: Essential Social Analysis Skills Course - external event
13 Nov 2019 NSW Branch: J.B. Douglas Awards Sponsorship
12 Nov 2019 WA Branch meeting: Prof Cathryn Lewis – Hansford-Miller Fellow 2019
12 Nov 2019 Time Series & Forecasting Symposium (TSF2019), Sydney - external event
8 Nov 2019 UQ Institute for Social Science Research: Program Evaluation Course
7 Nov 2019 Statistical Design and Analysis in Data Science - external event
7 Nov 2019 Statistical Design and Analysis in Data Science - external event
5 Nov 2019 WA Branch Young Statisticians: Meet up with Professor Cathryn Lewis (2019 Frank Hansford-Miller Fellow)
5 Nov 2019 Queensland Branch meeting - November
4 Nov 2019 CPD97- Network meta-analysis and population adjustment for decision-making - CPD97
31 Oct 2019 Vic Branch – Belz Dinner
31 Oct 2019 Vic Branch – Statistics is the Crown Jewel of Data Science (Belz Lecture)
28 Oct 2019 Webinar: An introduction to business analytics beyond statistical analysis
23 Oct 2019 SA Branch Meeting: Dr David Baird VSN NZ Ltd
21 Oct 2019 NSW Branch: October Event by Prof Elizabeth Stuart
21 Oct 2019 B&B Networking Event
21 Oct 2019 CPD105 - Propensity score methods for estimating causal effects in non-experimental studies: The why, what, and how
9 Oct 2019 SSA NSW Young Statisticians & Data Scientist Careers Networking
8 Oct 2019 WA Branch: Displaying Uncertainty and Risk - Dr John Henstridge
3 Oct 2019 Randomization, Bootstrap and Monte Carlo Methods in Biology - external event
1 Oct 2019 SSA-Event: YSC2019 Dinner - Kingston Hotel
1 Oct 2019 Queensland branch meeting: Automated Technologies for Systematic Review & Meta-Analysis
1 Oct 2019 SSA-Event: Young Statisticians Conference 2019
30 Sep 2019 CPD102 - SSA Canberra/YSC Event: Pre-Conference Trivia Night!
30 Sep 2019 CPD98- Communicating with R Markdown
30 Sep 2019 CPD103 - Maximising the use of Australian Bureau of Statistics Data Products and Analysis Tools
30 Sep 2019 CPD101- Mediation Analysis Using Potential Outcome Framework
26 Sep 2019 SA Branch Meeting: Peter Kasprzak
24 Sep 2019 NSW Branch: A notion of depth for curve data by Dr Pierre Lafaye de Micheaux
24 Sep 2019 Vic Branch – Young Statisticians Showcase 2019
23 Sep 2019 CPD106- Advanced R skills: Introduction to Shiny and Building R Packages
17 Sep 2019 SSA Webinar with Noel Cressie: Inference for Spatio-Temporal Changes of Arctic Sea Ice.
10 Sep 2019 WA Branch Meeting - Matt Schneider
5 Sep 2019 Applied Statistics and Policy Analysis Conference, 2019 - external event
3 Sep 2019 Queensland Branch meeting: Shiny showcase
28 Aug 2019 SA Branch Meeting - Dr Kathy Haskard
27 Aug 2019 Vic Branch – Detecting botnet activity using machine learning
20 Aug 2019 Talk on the QUT Digital Observatory
19 Aug 2019 Oceania Stata Conference - external event
18 Aug 2019 ISI 2019 – 62nd ISI World Statistics Congress - external event
13 Aug 2019 WA Branch Meeting - Joint IBS and SSA - Suman Rakshit
7 Aug 2019 SA Young Statisticians' Career Event
7 Aug 2019 2019 International Conference and Workshops on Survey Research Methodology - external event
6 Aug 2019 NSW Branch: Gender and Cultural Bias In Student Evaluations of Teaching at Universities by A/Prof Yanan Fan
24 Jul 2019 SA Branch Meeting - Dr Murthy N Mittinty
24 Jul 2019 The Research School on Statistics and Data Science 2019 (RSSDS2019) - external event
18 Jul 2019 Vic Branch - Tutorial on sequential Monte Carlo methods in statistics
18 Jul 2019 Minitab Insights Event Australia - external event
17 Jul 2019 Statistical Tools for the Pharmaceutical Industry - external event
9 Jul 2019 (Cancelled) WA Branch Meeting
9 Jul 2019 SSA-QLD Career Seminar: Lead With Statistics
7 Jul 2019 34th International Workshop on Statistical Modelling (IWSM2019) - external event
4 Jul 2019 Gaining skills in biostatistical consultancy- CPD94
3 Jul 2019 R skills workshops: R Markdown and Building R packages
2 Jul 2019 Tutorial on Sequential Monte Carlo methods in Statistics
1 Jul 2019 Computational and Applied Statistics (CAS 2019) - external event
30 Jun 2019 42nd Mathematics Education Research Group of Australasia (MERGA) Conference 2019 - external event
28 Jun 2019 Semiparametric regression with R - CPD99
26 Jun 2019 SA Meetup event: What went wrong with the polls? Do statisticians have a role to play?
25 Jun 2019 Vic Branch - Mentoring Breakfast
19 Jun 2019 Systematic reviews & meta-analysis of prognosis studies
11 Jun 2019 WA Branch Meeting - Dr Adriano Polpo - Hypothesis Tests: Using Adaptive Significance Levels for Decisions
11 Jun 2019 Data science helping to create a better justice system - an ACEMS Public Lecture at UTS
29 May 2019 SA Branch Meeting - Dr Beben Benyamin & Dr Ang Zhou
28 May 2019 Vic Branch – A recipe for quantifying the impact of prevention
28 May 2019 ICORS-LACSC 2019 - external event
16 May 2019 Fast algorithms and modern visualisations for feature selection - CPD96
14 May 2019 WA Branch Meeting - Young Statisticians Meeting
7 May 2019 QLD branch - Multimorbidity: Measurement for Health related Quality of Life and Health service use
7 May 2019 Chief Data & Analytics Officer Exchange - external event
4 May 2019 Data Day- Melbourne - external event
2 May 2019 Data Day- Sydney - external event
30 Apr 2019 Vic Branch – Reproducibility and Open Science
29 Apr 2019 Spatio-Temporal Statistics with R
17 Apr 2019 SA Branch Meeting - Professor Michael Sorich
9 Apr 2019 WA Branch Meeting - Prof Inge Koch
2 Apr 2019 QUEENSLAND ORDINARY BRANCH MEETING
2 Apr 2019 QUEENSLAND AGM
27 Mar 2019 SOUTH AUSTRALIA AGM
19 Mar 2019 Vic Branch – AGM + Statistics with industry: demonstrating impact
11 Dec 2018 Queensland Xmas Party
26 Sep 2018 Young Statisticians’ Workshop 2018
25 Sep 2018 Urban Modelling and Understanding with Machine Learning
11 Sep 2018 Young Statistician Careers Seminar
5 Sep 2018 Workshop: Semiparametric Regression with R with Matt Wand
28 Aug 2018 SSA Biostatistics Networking Event
26 Aug 2018 International Society for Clinical Biostatistics and Australian Statistical Conference 2018
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