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• Design and Analysis of Experiments course

  • Start
    13 Sep 2021
  •  
    (AEST)
  • End
    22 Sep 2021
  •  
    (AEST)
  • Location
    Online

  The Statistical Consulting Centre at the University of Melbourne is presenting this course, which covers the principles and practice of designing experiments or trials, and the analysis of data from them.

  The course covers the following topics:

  • choice of experimental units;
  • importance of randomisation, and the practicalities;
  • replication and sample size;
  • blocking and matching;
  • commonly used designs, including completely randomised designs, randomised block and matched pair designs, Latin square designs;
  • treatments, including factorial structures;
  • analysis of data from designed experiments;
  • analysis of variance and covariance;
  • special designs, including incomplete block designs, split-plot designs, and fractional factorial designs;
  • transformations of data;
  • practical and ethical issues arising in the conduct of experiments.

  
  

  Course presenter:

  The presenter is Associate Professor Graham Hepworth, Consultant for the Statistical Consulting Centre in the School of Mathematics & Statistics. Graham has had extensive experience over three decades in design and analysis of experiments, in fields such as forestry, horticultural science, animal studies, medicine (randomised controlled trials), industry and the social sciences.

  Course structure:

  This online course runs over five mornings on alternate days. Each day will commence at 9:00 a.m. and finish at 12.30 p.m. The sessions will mix lecture presentations with practical exercises.   The statistical package Minitab will be used in the course. However, the course will not be package-centred, and no prior experience with Minitab is necessary.

  Who should take this course?

  The course is suitable for anyone involved in the design and analysis of research experiments. Applications include randomised trials in medicine or the social sciences, designed experiments in the biological sciences, studies of processes in engineering, as well as many possibilities in other disciplines.

  Prerequisites:

  Participants should have some understanding of statistics at an introductory level. For example, it would help to know something about hypothesis tests and confidence intervals, and, preferably, analysis of variance. The course "Statistics for Research Workers" conducted by the Statistical Consulting Centre would be ideal preparation.

  Cost and enrollment details:

  Cost $880 (incl. $80 GST).

  The University of Melbourne graduate researcher student $660.

  The fee includes a comprehensive set of notes.

  A certificate on completion can be provided on request.

  To register click here.
  

   

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• SSA Vic: Industry Showcase Night

  • When
    21 Sep 2021
  •  
    5:00 PM - 7:00 PM (AEST)
  • Location
    Online

  Register

  For this event, we have the pleasure of hosting a handful of inspiring early career speakers and mid-career speakers, working in industry, who will speak on their experiences. The speakers have been invited to share what they’ve learned, what they’ve achieved, what they’ve enjoyed and what surprised them, as well as, perhaps, what they don’t like, what they haven’t learned, and so on. We also have a number of senior industry speakers who have been invited to provide their sage advice, their insights and general guidance to those interested in developing a fruitful career in industry.

  Each speaker will give a 10 minute talk, followed by a panel discussion of about 30 minutes. There we will do some socialising, as well as have an opportunity for audience members to freely approach each other and the speakers.

  
  

  Anna Quaglieri 

   

  Bioinformatics Data Scientist at Mass Dynamics

  Anna has an academic background in Statistics, completed between the universities of Bologna, Glasgow and Melbourne. Once in Melbourne, she joined the WEHI where she did her Masters research in Population Genetics, and PhD in Cancer Genomics. She then worked for 1.5 years as a Data Scientist for the AI consulting company Eliiza. Two months ago she joined the Melbourne based startup Mass Dynamics where she is working as a Bioinformatics Data Scientist. At Mass Dynamics Anna develops workflows for the analysis of mass spectrometry data, with the aim of helping more life scientists transform proteomics data to knowledge.

  
  

  Kohleth Chia  

  
  

  Data Scientist Lead at Bunnings

  Kohleth is a Data Scientist Lead at Bunnings. He is also an Accredited Statistician (AStat). His decade of experience in statistics / data sciences span across government, research institution, and industry.

  Stephen Bush  

  

  Principal Optimisation Analyst at SEEK

  Steve is a Principal Optimisation Analyst at SEEK, where he leads the Experimentation team. He has a PhD in Mathematics from the University of Technology Sydney. His specialisation is the efficient design of experiments and is interested in the use of experimentation at scale to enable data driven decision making and providing advice on evaluation, measurement and statistical methods.
  

  Denzel Florez

  

  Senior Analyst (Model Risk Management) at Macquarie Group

  Denzel is a model risk analyst at Macquarie Group, performing model validation to ensure financial models comply with regulatory requirements. This involves reviewing statistical models and assessing whether model assumptions are suitable for their purpose. Denzel graduated in 2018 with Honours in Statistics from the University of Sydney.

  Belinda Maher

  

  Senior Public Transport Planner

  Belinda Maher started her journey in transport data a decade ago at KiwiRail, where she worked on a $2 billion NZD upgrade of Auckland's suburban train network. After returning home to Melbourne, she took up a role at Public Transport Victoria in Operational Performance Analysis.

  She now works in Network Planning at the Department of Transport (DoT) where she is involved in data-driven planning and data visualisation (including mapping).

  At DoT, Belinda has worked on projects including analysing observed tram speeds across the network for on-road priority planning, and also on collating and mapping data about current and future train stations for strategic planning.

  In 2021 Belinda guest lectured at Monash University in the subject Wild Caught Data, and she has previously presented to Melbourne (and Auckland) R-Ladies and the Melbourne Users of R Network.
  

  Steph Stammel

  

  Principal Econometrician 

  Steph provides strategy and advice to data science teams looking to leverage their current skills and take their companies to their next level in analytics. She is a Ph.D. data scientist with nearly 12 years' experience in the field. She is also an expert modeller and test designer, extensive fieldwork in randomised controlled designs, a strong research background.

  Current fun projects include the application of weak AI-type agents and algorithms to classical forecasting models at scale, designing and delivering tools for smoothing the transition for new R users and setting up the new R-Ladies Remote chapter.

  
  

  
  

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• Storytelling with Data Visualisation

  • Start
    23 Sep 2021
  •  
    (AEST)
  • End
    24 Sep 2021
  •  
    (AEST)
  • Location
    Online

  ACSPRI is offering a two day workshop.

  Studies have shown that readers will only spend 3 to 8 seconds looking at each plot in a report before deciding whether to invest more time examining that plot or to move on to the next part of the report.

   

  This master-class has two objectives – to teach the design principles required to make plots that really have an impact on the reader, and to teach the practical skills required to create these plots within the R software package.

   

  Consider the two plots below. In which plot can you easily see the pattern the author wants to convey within the plot, and what you should do as a result of the plot?”

   

  

   

   

  

   
  

  This course will be run over 2 days in three sessions per day:
   

  • 9.00am - 10.30am - Session 1
  • 11.30am - 1.00pm - Session 2
  • 2.00 - 4.00pm - Session 3: exercises and consultation

   
  Exercises will be provided and there will be opportunities for consultation with Mark in the afternoon sessions.

  Instructor: 

  

  Dr Mark Griffin is the Director of ResearchStats, which is a Division of Insight Research Services Associated (www.insightrsa.com). ResearchStats provides training and consulting in statistics for academic audiences. Mark is also an Industry Fellow with the School of Business, University of Queensland, and has established and written training materials for several of their courses in Business Analytics. Mark serves on the Executive Committee for the Statistical Society of Australia, and is Founding Chair of their Section for Business Analytics. Mark is also the Founding Chair of the Business Analytics Special Interest Group within the International Institute of Business Analysis. To date he has presented over 100 two-day and 30 five-day workshops in statistics around Australia.

  Recommended Background: 

  Some basic familiarity with the R software package is expected prior to the workshop. The participant does not need to have any previous experience using R for data preparation or data visualisation. No knowledge of statistics is required.

  Recommended Texts: 

  If students would like a head start in using R for data visualisation they may choose to look at: https://r-graphics.org/

  For more information please click here. To Register click here.

   

   

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• Towards Higher-Dimensional Spatial and Spatio-Temporal Extremes - cancelled

  • When
    24 Sep 2021
  •  
    4:00 PM - 5:00 PM (AEST)
  • Location
    Online

  NIASRA and the SSA Environmental Statistics section present the following seminar: Towards higher-dimensional spatial and spatio-temporal extremes- with Dr Jenny Wadsworth (Lancaster University)

  Unfortunately this event had to be cancelled.
  

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• Mathematics without Borders - The Centennial of the International Mathematical Union

  • Start
    27 Sep 2021
  • End
    28 Sep 2021
  • Location
    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. 

  
  
  

  
  

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• Queensland Branch Meeting: Statisticians and the reproducibility crisis

  • When
    28 Sep 2021
  •  
    4:30 PM - 6:00 PM
  • Location
    Zoom

  Register

  Please join us online for the September Queensland Branch Meeting! There will be a branch meeting at 16:30 followed by a seminar-discussion at 17:00.

  When: 4:30 PM - 6:00 PM (AEST)

  Tuesday 28th September 2021

  Location: Online - Zoom

  Statisticians and the reproducibility crisis

  Abstract: Statisticians play a key role in almost all scientific research, and so are also key to tackling the reproducibility crisis which is undermining the value of much scientific research. Our role may be particularly important given that many problems with irreproducible papers are due to problems in the study design, statistical analysis and interpretation of results. We must promote more efficient, replicable and credible science, starting today, by being the role-model statisticians that we need for tomorrow.

  Our four speakers will give their perspective on statistics and the reproducibility crisis, and also give their opinions on how statisticians can help improve the quality of research. We hope to have at least 20 minutes for discussion after the speakers' presentations, so please come along and share your thoughts on this hugely important topic.

  Speakers:

  Dr Sabine Hoffmann is a postdoctoral researcher at the Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig-Maximillans-University of Munich. Sabine’s research projects investigates the effects of fishing for significance on statistical inference, and methods that allow handling of results variability when applying alternative analytical strategies. Sabine conveys these ideas in her consulting activities in order to raise awareness on how common research practices can have devastating effects on the replicability of research findings.

  Dr John Maindonald is a retired visiting research Fellow at the Centre for Mathematics and Its Applications, Australian National University (ANU). John has 50 years of experience collaborating and consulting with organisations and scientists across a wide range of application areas. Some of his research interests include statistical computation, statistical perspectives on data mining, use of R for practical data analysis, research planning and population genetics.

  Dr Teresa (Terry) Neeman is a biostatistician with the Biological Data Science Institute, ANU College of Science. She has more than two decades of experience as a biostatistician working with biologists, biomedical researchers and clinicians in both industry and academia. Terry enjoys the statistical challenges associated with all aspects of experimental work; from experimental design to data exploration and statistical modelling. Over the last several years, she has worked more closely with bioinformaticians, and has developed a strong interest in tools for visualisation and inference of highly complex data.

  Prof Adrian Barnett is the Program Lead – Statistics in Health Services at the Australian Centre for Health Services Innovations, QUT. He has spent more than 21 years working as a statistician, specialising in biostatistics, health services research and the research funding. He is particularly passionate about the application of statistics to health and the use of data analysis to develop cost-effective interventions within the health sector.

  Moderator: A/Prof. Dimitrios Vagenas

  
  

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• Joint SSA Canberra + Canberra Data Scientists Meeting - Using Data Analytics for Audits

  • When
    28 Sep 2021
  •  
    5:30 PM - 6:30 PM (AEST)
  • Location
    Virtual via Microsoft Teams

  SSA Canberra invites you to its September branch meeting, which will be joint with Canberra Data Scientists

  Times (+/- some standard errors):  

  5:30pm – 6:30pm AEST (please note the earlier starting time at request of the speaker): Presentation on MS Teams

  RSVP: No RSVP will be required for this meeting, and please see below for the link. If you are worried MS Teams will encounter teething problems on your machine, please try out the meeting link at the bottom of this email, and if you have any questions that the internet cannot resolve (please also see this help page), please email Francis Hui at ssacanberra@gmail.com.

  Speaker: Ms. Xiaoyan Lu, Acting Executive Director, Australian National Audit Office (ANAO)

  Title:  Using Data Analytics for Audits

  Abstract: In this talk, Ms. Lu will share 

  • how data analytics is applied in the audit context;
  • her experience and lessons learned of establishing data analytics teams and delivering data analytics strategy in government agencies; and
  • what capabilities that employers are after when recruiting data scientists and analysts.  

   

  Biography: Ms. Xiaoyan Lu has over 20 years’ experience in research and analytic industry and is an Acting Executive Director of the System Assurance and Data Analytics (SADA) Group at the Australian National Audit Office (ANAO). SADA provides IT audit and data analytics support and advice to all audit service groups within the ANAO. She joined the ANAO in April 2018 to build the Data Analytics team and deliver the Data Analytics Strategy 2018-20. She was awarded the Australia Day Achievement Medallion in 2020 in recognition of her leadership in transforming the delivery of audit outcomes through data analytics, commitment to development and mentoring of staff and her dedication and commitment to innovation and excellence. Prior to that, she was a Director at the Australian Sports Commission leading initiatives on data driven decision making in the sport sector, and worked there for 11 years. Before joining the public sector, she had worked in the academic, NGO and private sectors for providing research consultancy for eight years. Xiaoyan received a Bachelor degree in Science from Beijing Normal University, a Master degree in Environmental Science from Peking University, and a Master degree in Applied Statistics from Australian National University.

  
  

  **Microsoft Teams meeting link**

  Join on your computer or mobile app

  Click here to join the meeting

  This will bring up Teams in your default browser, even if you do not have the Microsoft Teams software installed.

  Note that, unlike Zoom, everyone by default sits in a waiting room and only comes in when the organiser comes in. 

  If you encounter any issues with MS teams and cannot find a solution online (please also see this help page), you can email Francis at ssacanberra@gmail.com or Yanchang Zhao at Yanchang.Zhao@data61.csiro.au

   

  Or call in (audio only)

  +61 2 9053 9802,,96171836#   Australia, Sydney

  Phone Conference ID: 961 718 36#

   

  For more information on joining Microsoft Teams meetings

  Learn more

   

  
  

  Website links: 

  https://statsoc.org.au/Canberra-Branch-meetings

  
  

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• SSA NSW Branch: Sieve bootstrap memory parameter in long-range dependent stationary functional time series by Prof. Hanlin Shang

  • When
    29 Sep 2021
  •  
    6:00 PM - 7:00 PM (AEST)

  This month we are very pleased to have Prof. Hanlin Shang from Macquarie University to present his recent work about sieve bootstrap and functional time series.
   

  Please note for security reasons, you will need to register in advance for this meeting: https://macquarie.zoom.us/meeting/register/tZEvceuhrT0tE9PY0vtRKVWW8LNbX0hMmBsg
  
  After registering, you will receive a confirmation email containing information about joining the meeting.

  Any questions, please feel free to contact: secretary.nswbranch@statsoc.org.au
  

  Date: Wednesday, 29th September 2021
  
  Time: 6:00pm - 7:00pm (AEST)
  
  Prof. Hanlin Shang
  Macquarie University, Sydney
  
  Sieve bootstrap memory parameter in long-range dependent stationary functional time series
  
  Abstract:
  We apply a sieve bootstrap procedure to quantify estimation uncertainty of long-memory parameter in stationary functional time series. To estimate the long-memory parameter, we use a semiparametric local Whittle estimator, where discrete Fourier transform and periodogram are constructed from the first set of principal component scores, via a functional principal component analysis. The sieve bootstrap procedure uses a general vector autoregressive representation of the estimated principal component scores. It generates bootstrap replicates that adequately mimic the dependence structure of the underlying stationary process. For each bootstrap replicate, we first compute the estimated first set of principal component scores and then apply the semiparametric local Whittle estimator to estimate the memory parameter. By taking quantiles of the estimated memory parameters from these bootstrap replicates, we can construct confidence intervals of the long-memory parameter. As measured by coverage probability differences between the empirical and nominal coverage probabilities at three levels of significance, we demonstrate the advantage of using the sieve bootstrap in comparison to the asymptotic confidence intervals based on normality.
  
  Biography:
  Hanlin is a Professor of Business Analytics at the Department of Actuarial Studies and Business Analytics, Macquarie University. Hanlin’s research interests include inference, modelling and forecasting functional time series.

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• CPD139-An Introduction to Bayesian Modelling Using Greta

  • Start
    16 Nov 2021
  •  
    1:00 PM (AEDT)
  • End
    17 Nov 2021
  •  
    5:00 PM (AEDT)
  • Location
    Online
  • Spaces left
    2

  Register

  The NSW Branch of the SSA is offering this two day workshop.

  Often, statistical analyses require custom models that cannot be fitted using off-the shelf statistical software, but can be estimated by MCMC by specifying the model in specialised software, the most popular of which are BUGS, JAGS and Stan.  Greta is a package for statistical modelling in R that has three core differences to these available alternatives:

   1. simple: greta models are written right in R, so there's no need to learn another language like BUGS or Stan

  2. scalable: greta uses Google TensorFlow so it's fast even on massive datasets, and runs on CPU clusters and GPUs

  3. extensible: it's easy to write your own R functions and packages using greta

  We will start with simple linear models on real ecological data, and gradually expand the models to be more complex and better represent the data. We will also have time at the end of the course to discuss fitting models specific to your own work - so feel free to bring along a problem you’d like to discuss!

  Presenter:

  

  Professor Nick Golding is an infectious disease modeller with a focus on globally-important pathogens. His work combines mathematical and statistical modelling, ecology, public health, and research software engineering. Since completing a PhD on mosquito ecology, he has developed models and maps of the risk posed by some of the world’s most important and neglected diseases – including malaria, Dengue fever, Chikungunya, Ebola, and COVID-19. He has a preference for semi-mechanistic Bayesian models applied to large, noisy datasets and developed the greta R package to handle both the scale and uniqueness of these types of models.
  
  Dr. Nick Tierney completed his undergrad and honours in Psychological Science, then took an unconventional turn into a PhD in Statistics. He now works as a research software engineer with Dr. Nick Golding at the Telethon Kids Institute. He is currently working on improving and maintaining the greta (https://greta-stats.org/) R package for statistical modelling. He is also interested in implementing workflows to automate data analysis.  Dr. Tierney’s research interests are broad, but centred around improving data analysis. This includes exploratory data analysis, statistical modelling, diagnostics, and understanding how colour choice can impact decision making. Dr. Tierney is a strong believer in free and open source software, and has written several popular R packages to improve data analysis, which can be seen on his software page: http://njtierney.com/software. 

  Requirements:
  

  This course is designed for those who want to learn how to do Bayesian modelling using the greta software. We assume users have the following background/experience:

  • Familiarity with R
  • Experience using linear models

  A rudimentary understanding of Bayesian inference

  We recommend trying to install the software from github on your laptop/machine ahead of time with remotes::install.github("greta-dev/greta") but we will also provide virtual environments to use in the course. Course materials will be made available online.

   After this course you will be able to:

  • Fit and predict from Bayesian generalised linear models in greta
  • Check model convergence and fit (including prior and posterior predictive checks)
  • Summarise MCMC outputs
  • Be able to fit more advanced models including mixture and hierarchical models
  • Create visualisations and tables of the model outputs for use in understanding model fit and for publication.

  
  

  Cancellation Policy:

  Cancellations received prior to Thursday, November 11, will be refunded, minus a $20 administration fee. From then onward no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to events@statsoc.org.au.

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• Australian Trials Methodology Conference 2021

  • Start
    6 Dec 2021
  •  
    (AEDT)
  • End
    7 Dec 2021
  •  
    (AEDT)
  • Location
    Online

  This event is being convened by the Australian Trials Methodology (AusTriM)

  The organising committee warmly invite you to join us at our first Australian Trials Methodology Conference, which will take place fully online over the 6th and 7th of December 2021.

  The meeting program will showcase cutting-edge trial design and analysis approaches in a way that is thought-provoking yet still accessible to bio-statisticians, methodologists and trialists (across any clinical discipline) alike.

  
  

  Invited Sessions

  Opening Plenary Stephen Senn (UK/CH) Marcel Wolbers (CH)
  Novel Trial Design Susan Murphy (US) Elaine Pascoe (AU) Tom Snelling (AU)	Trial Analysis Dimitris Rizopoulos (NL) Suzie Cro (UK) Ian White (UK)	Cluster Randomised Trials Fan Li (US) Charles Weijer (CA) Phillip Westgate (US)

   

   

  Registration

  Registration type	Price
  Standard	$200
  Student	$100

   

  Abstract Submission

  The Scientific Program Committee are now accepting abstracts for oral presentations. It is anticipated that presentations will be 15 minutes in length (subject to change). We welcome any submissions which focus on innovative clinical trial design or analysis methodology. Please see the event website for further details.

   

  Key dates

  Submissions open	Monday 16th August
  Submissions close	Friday 17th September
  Authors notified	Friday 22nd October

  
  To register please click here.
  

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• CPD140 - Data Visualisation with R

  • When
    6 Dec 2021
  •  
    9:00 AM - 5:00 PM (AEDT)
  • Location
    Online
  • Spaces left
    37

  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.

  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 will teach you how to create production-ready graphics using the grammar of graphics implemented in ggplot2 R-package. In addition, the workshop 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 focusing 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:

  This workshop is suitable for those who know R but are not familiar or comfortable with using ggplot2 or would like a refresher on ggplot2. It 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:

  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

  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:

  • 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

  Desirable:

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

  • Some familiarity with tidyverse

  TimeTable: 

  09:00 – 10:30 (1.5 hours)	Session 1
  10.30 – 11:00	Break
  11:00 – 12:30 (1.5 hours)	Session 2
  12:30pm - 1.30pm	Break
  1:30 - 3:00 (1.5 hours)	Session 3
  3:00 - 3:30	Break
  3:30 - 5:00 (1.5 hours)	Session 4

   

  Cancellation policy:

  Cancellations received prior to 1 Dec 2021 will be refunded, minus a $20 administration fee. From then onward no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to eo@statsoc.org.au..

  
  

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• ACSPRI's 2022 Summer Program

  • Start
    17 Jan 2022
  •  
    (AEDT)
  • End
    18 Feb 2022
  •  
    (AEDT)
  • Location
    Online

  ACSPRI's 2022 Summer Program is offering courses over 4 weeks in January and February 2022. 

  • Classes will run across 2 to 5 days in blocks of 'online time'.
  • Classes will be restricted to 12 people to maintain the interactivity and applied nature of our courses.
  • Depending on the course, you will receive reading, notes and general information about the course in advance.
  • All other software requirements will be listed on the course page & we will contact you in advance to make sure you have what you need.
  • Prior to to the course, we will offer you an opportunity to test your setup with ACSPRI support staff.
  • We understand that networking is a very important part of your ACSPRI experience, over the week, there will be ample opportunities to interact with your fellow classmates and instructor as well as work on applied exercises.

  
  

  Courses in this program:

  Level	Week	Venue	Title	Status
  Level 1	Week 1	ONLINE	Introduction to Computer-assisted Qualitative Data Analysis using Nvivo: Online	Open
  Level 1	Week 1	ONLINE	Introduction to Qualitative Research: Online	Open
  Level 2	Week 1	ONLINE	Data Analysis Using Stata: Online	Open
  Level 2	Week 1	ONLINE	Fundamentals of Program Evaluation in Public Policy: Online	Open
  Level 3	Week 1	ONLINE	Fundamentals of Structural Equation Modelling: Online	Open
  Level 5	Week 1	ONLINE	Multi-level Analysis using Mplus: Online	Open
  Level 1	Week 2	ONLINE	Foundations of Qualitative Methodologies, Data Collection and Analysis Online (3-Day)	Open
  Level 1	Week 2	ONLINE	Fundamentals of Statistics: Online	Open
  Level 1	Week 2	ONLINE	Introduction to Social Network Research and Analysis: Online	Open
  Level 2	Week 2	ONLINE	Data Analysis in R: Online	Open
  Level 2	Week 2	ONLINE	Qualitative Research: Design, Analysis and Representation: Online	Open
  Level 3	Week 2	ONLINE	Applied Longitudinal Data Analysis: Online	Open
  Level 4	Week 2	ONLINE	Applied Structural Equation Modelling: Online	Open
  Level 2	Week 3	ONLINE	Applied Statistical Procedures: Online	Open
  Level 2	Week 3	ONLINE	Fundamentals of Multiple Regression: Online	Open
  Level 2	Week 3	ONLINE	Qualitative Comparative Analysis (QCA): An Introduction (Online - 3 Day)	Open
  Level 3	Week 3	ONLINE	Advanced Statistical Analysis Using R: Online	Open
  Level 3	Week 3	ONLINE	Big Data Analysis for Social Scientists : Online - (3 Day)	Open
  Level 5	Week 3	ONLINE	Advanced Structural Equation Modelling: Online	Open
  Level 2	Week 4	ONLINE	Qualitative Comparative Analysis (QCA): An Application in 10 Steps (Online - 4 Day)	Open

  
  

  How to enroll: 

  Step 1: Log in to the ACSPRI website (you can create an account or request a new password if required). The account should be in the name of the person taking the course. Alternative billing details (e.g. for a Finance Officer) can be entered later if need be.

   Step 2:  Check the status of the desired course. If places are available the status will show up as "Open". If the course is "Full" you will be able to join the waiting list for that course. You would then be contacted via email if a place becomes available or a second course is offered.

   Step 3: Select the title of the desired course to see the course outline page.  Select "Add to cart" and proceed to checkout.

   Step 4: Enter billing details (e.g. yourself or an admin/finance officer). Enter shipping details (course notes will be mailed to this address), and either finalise payment by credit card or request an invoice by selecting 'Direct Deposit', (please keep in mind the relevant payment deadlines).

   Step 5: Click "Review Order" to check the details and then submit order.

   Step 6: Check your invoice/receipt (under the course title) to see if your course has been confirmed to run at the program. If it has not yet been confirmed, you will receive an email when a sufficient number of bookings has been received and the course has been confirmed.

  For more information click here.
  

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• Joint Southern Statistical Meetings 2022 (JSSM2022)

  • Start
    27 Jun 2022
  •  
    (AEST)
  • End
    1 Jul 2022
  •  
    (AEST)
  • Location
    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! 
  

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• ICM 2022 - external conference

  • Start
    6 Jul 2022
  •  
    (AEST)
  • End
    14 Jul 2022
  •  
    (AEST)
  • Location
    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
  

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• XXXI International Biometric Conference (IBC 2022) - external event

  • Start
    10 Jul 2022
  •  
    (AEST)
  • End
    15 Jul 2022
  •  
    (AEST)
  • Location
    Riga, Latvia

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

  
  

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• Australasian Applied Statistics Conference 2022

  • Start
    28 Nov 2022
  • End
    2 Dec 2022
  • Location
    RACV Inverloch Resort, Victoria, Australia

  The details can be found here: https://aasc2022.netlify.app/

  The workshop will be held on Mon 28th Nov 2022. 

  The conference itself is to be held on Tue 29th Nov to Fri 2nd Dec 2022. 

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• IBS-AR Biometrics Conference

  • Start
    27 Nov 2023
  • End
    1 Dec 2023

  The conference will be joint with SEEM at Bay Of Islands in New Zealand.

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