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StatChat is back!
This is an SSA members session to discuss statistical issues. Bring your questions and come to discuss and/or listen. Julie Simpson is our guest senior statistician for this month.
Registration is free.
Title: Estimating a Covariance Function from fragments of Functional Data
Abstract: Functional data are often observed only partially, in the form of fragments. In that case, the standard approaches for estimating the covariance function do not work because entire parts of the domain are completely unobserved. In previous work, Delaigle and Hall (2013,2016) have suggested ways of estimating the covariance function, based for example on Markov assumptions. In this work we take a completely different approach which does not rely on such assumptions. We show, that using a tensor product approach, it is possible to reconstruct the covariance function using observations located only on the diagonal of its domain.
Short Bio of the Presenter: Aurore Delaigle is a professor of statistics at the University of Melbourne. She is elected fellow of the Australian Academy of Science, a fellow of the American Statistical Association, a fellow of the Institute of Mathematical Statistics, and an elected member of the International Statistical Institute. She work primarily on nonparametric curve estimation and functional data analysis, where her main interest is in data observed imperfectly such as data observed with measurement errors, data observed in a aggregated way, or data on partially observed. She is particularly interested in techniques for reducing functions to low-dimensional vectors, and in partially observed curves.
Zoom Link of this presentation
Url to join: https://adelaide.zoom.us/j/86265863018?pwd=NmZkOU55UFhrVXZkQ1NCci80ZmhnZz09&from=addon
The Early Career and Student Statisticians Network is excited to be hosting a Science Communication Workshop Series in the lead up to ECSSC2021.
Join us virtually to learn essential science communication skills from the experts across four (4) exciting workshops covering:
We hope participants will come away from the series with the confidence to share their research in an engaging manner.
About workshop 3: Honing Your Pitch
Discover techniques to effectively convey your research in a short period of time. In this interactive workshop, Dr Will Grant will cover how to concisely present what you do, how you do it and why without losing the importance of your work.
About the presenter: Dr Will Grant
Dr Will Grant is Senior Lecturer in Science Communication at the Australian National Centre for the Public Awareness of Science at ANU. Awarded for his public policy and outreach work, Will has authored or co-authored dozens of works in various scholarly outlets (including Public Understanding of Science, Environmental Communication, Computers in Human Behaviour, Scientometrics and Higher Education Policy), and written commissioned and pitched articles and opinion pieces in high impact public facing outlets (including The Guardian, The Sydney Morning Herald, The Australian, The Conversation, Times Higher Education, The Canberra Times, The Brisbane Times, Crikey, The Drum, Climate Spectator and ABC Environment), focusing mostly on the interaction of science, politics and technology. He is co-founder of the researcher employment service PostAc.
Will is regularly heard on Radio National discussing science for Research Filter and Nightlife, as well as podcasting in The Wholesome Show and G’day Patriots , both of which have charted in the Australian iTunes top 50. Will has held science communication workshops for a range of Australia’s leading science organisations, including Universities Australia, Science and Technology Australia and the Australian Academy of Science, as well has various universities and research institutes, government departments and scientific societies around the country. He tweets at @willozap.
This event is free for registered delegates of ECSSC. If you are registered for ECSSC, please contact Jodi Phillips, SSA's Events Coordinator, for your booking code.
Cancellation Policy: Cancellations received 7 days prior to the workshop will be refunded. From then onwards no part of the registration fee will be refunded. However, registrations are transferable within the same organisation.
If you have any questions, please contact us.
The Bayesian Section of SSA proudly presents the following webinar:
A Desingularized Mean Field Approximation
presented by Dr Susan Wei (DECRA fellow, University of Melbourne).
About the webinar:
It is well known that the posterior distribution over neural network weights can be approximated by neither a Gaussian nor a Gaussian mixture distribution. Rather, as established in singular learning theory, the posterior distribution over the parameters of a singular model is, asymptotically, a mixture of standard forms. Namely, there exists a partition of the parameter space such that in each local parameter set, the average log likelihood ratio can be made "normal crossing" via an algebraic geometrical transform known as a resolution map. We leverage this under-appreciated result to propose a generalized gamma mean-field variational family which can recover the leading term of the (normalized) log evidence. Affine coupling layers are employed to learn the unknown resolution map, effectively rendering the proposed methodology a normalizing flow with the generalized gamma as the source distribution, rather than the multivariate Gaussian typically employed.
Abut the presenter:
Presenter: Dr Susan Wei (DECRA fellow, University of Melbourne)
Susan Wei is a lecturer in the School of Mathematics and Statistics at the University of Melbourne. She currently holds a Discovery Early Career Researcher Award (DECRA) from the Australian Research Council (ARC). Her research interests include statistics, machine learning, and deep learning.
The event is free for members of SSA, but you do need to register.
The International Symposium on Forecasting (ISF) is the premier forecasting conference, attracting the world's leading forecasting researchers, practitioners, and students. Through a combination of keynote speaker presentations, academic sessions, workshops, and social programs, the ISF provides many excellent opportunities for networking, learning, and fun.
Important Dates 2021:
Invited Session Proposals: March 1
Abstract Submissions: March 15
Travel grant applications: March 15
Early Registration: May 3
For abstract submissions click here.
To learn more click here.
The 2021 World Meeting of the International Society for Bayesian Analysis (ISBA
2021) will be held online from 28 June to 2 July 2021. Registration will be free to
everyone before 1 May 2021. The deadline for abstract submissions is 15 March.
For more information and to register, click here.
We now have our 2021 Winter Program, master classes and workshops up on our website and ready for enrolments. You can visit our website and enrol in classes scheduled from March to October. We will be adding more short courses throughout the year.
Considering the potential for travel and gathering restrictions, our 2021 Online Winter Program & short courses will be offered 'live' online using Zoom. A reminder that courses will be capped at 12 people, so enrol now to secure a place and take advantage of the early-bird enrolment rate.
If you ever need to speak to us or are after more information, please call 03 8376 6496 or you can email us at firstname.lastname@example.org.
June 28- July 2
Foundations of Qualitative Methodologies, Data Collection and Analysis Online (3-Day)
Fundamentals of Statistics: Online
Introduction to Social Network Research and Analysis: Online
Fundamentals of Program Evaluation in Public Policy: Online
Applied Longitudinal Data Analysis: Online
Applied Structural Equation Modelling: Online
Applied Computer-assisted Qualitative Data Analysis using Nvivo: Online
Applied Statistical Procedures: Online
Data Analysis in R: Online
Data Analysis Using Stata: Online
Qualitative Research: Design, Analysis and Representation: Online
Big Data Analysis for Social Scientists : Online - 3 Day
Multi-level Analysis using Mplus: Online
Introduction to Qualitative Research: Online
Fundamentals of Structural Equation Modelling: Online
Questionnaire Design: Online April 15-16
A two day workshop focusing on building hard copy or internet surveys to meet a variety of needs. Topics include uses of surveys, constructing survey questions that are clear and unbiased, the need to match attitudinal or behavioural data collection with the purpose of the survey, and combining objective and open-ended questioning in order to enhance the usability of results.
NVivo Essentials: Online April 22-23
This workshop is aimed at providing researchers with essential skills in using NVivo software. Those choosing to enrol in this course will be working on or about to embark on a research project. The course assumes no prior skills with using NVivo, however will cater for all levels of participants, from novice to advanced users. The focus is on developing the essentials skills from NVivo through hands-on experience.
Creating and Managing Web surveys using LimeSurvey: Online April 28
LimeSurvey is a powerful web based survey tool . This course will introduce you to the LimeSurvey administrative interface, show you how to set up, conduct and export your data for a web based survey. You will cover methods for inviting and managing participants, managing and monitoring ongoing surveys and exporting data to multiple statistical packages.
NVivo for a Literature Review: Online (1-day)
NVivo can be a powerful tool to help you conduct your literature review in an effective and efficient way. This 1-day master-class introduces NVivo, and takes researchers through the process of sorting and organise literature and notes from readings in a systematic way. By the end of the workshop attendees will have a basic understanding on how to use and get the most out of their literature use NVivo
Structural Equation Modelling using Stata: Online May 7-8 (Fri-Sat)
A foundation for those of you wanting to use SEM to explore and test complex relationships. This 2-day master-class is designed for participants with an introductory-level understanding of the statistical methods of regression analysis and exploratory factor analysis. You will experience hands-on SEM examples and build your own Stata SEM models.
Collecting, Managing and Analysing Qualitative INTERVIEW Data: Online May 10-11
A practical course, enabling participants to understand the preparatory requirements for both individual and group qualitative interviewing as well as to become proficient in qualitative question design. Experience in both types of qualitative interviewing will be provided as well as practise in undertaking analyses of these types of data.
Applied Qualitative Interviewing Methods: Online May 18
A hands-on advanced qualitative interviewing workshop where you will have the opportunity to reflect on your data collection, revise the way you frame your questions, redesign your interview protocol, and practise interview behaviours through role-played mock interviews, allowing you to critically review any interview protocol and elicit deep, meaningful data from your participants.
Spatial Analysis in R: Online August 16-17 (NEW course)
Designed for applied users of R who want to take their spatial analysis to a higher level, this master-class will show you how to access spatial data from a number of sources, match this with geographic shape files, analyse spatial patterns, link these data to information from surveys, and create interactive maps to highlight important findings.
Storytelling with Data Visualisation: Online September 20-21
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 workshop has two objectives – to teach the design principles required to make plots that really stand out for the reader, and to teach the practical skills required to create these plots within R.
Qualitative Research: Doing Constructionist Data Analysis: Online October 4-7*
This master-class offers lectures and data workshops covering the latest approaches to key areas of qualitative research:
• Improving the quality of interview data analysis;
• Finding sequences in your data;
• Documents and digital data as social constructions;
• Theorising with qualitative data.
*Please note this will be an evening course running from 7pm to 9.30pm as Prof David Silverman is in the UK.
Foundations of R for Research: Online October 15-16
A step by step interactive introduction for people with no experience with R and RStudio.
Notes and exercises will cover a variety of data sets which you will work on during lectures and individually. The course content is particularly suited for those involved in research in the business, education, social and health sciences.
Trends, Challenges and the Art of Survey Writing for the Public Sector, NFP and Industry Research: Online October 25-26 (NEW Course)
Taught by instructors with real-world experience as campaign consultants, survey researchers and data scientists, this masterclass will focus on teaching you about survey design. You will be shown how political survey research works, and sometimes doesn’t, how technology and social trends are changing survey research, and the best ways to write effective survey questions.
Membership Services, Marketing and Events Coordinator
Australian Consortium for Social and Political Research Inc.
+61 3 8376 6496
Find out more.
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!
This is an invitation to submit a contribution for the:
Workshop of the 21st International Conference on Computational Science and Applications will be held on July 5-8, 2021, in Cagliari, Italy.
Like last year, ICCSA 2021 offers the possibility of online-only participation (with reduces registration fees). But we are also planning to offer the possibility of in-presence participation, should the pandemic situation allow it, by setting up a blended experience for mixed online/in-presence sessions.
The aim of CAS workshop is to bring together scientists working in computational statistics, scientific computation and applications in all areas of sciences, engineering, industry, economics, life sciences and social sciences.
Topics of interest include (but are not limited to):
* Computational Statistics: new issues in the design of computational algorithms for implementing statistical methods, development in R, etc
* Applications: statistical case study in all areas of sciences, engineering and industry, including economics, medicine, biology, earth sciences and social sciences.
All accepted papers will be included in the Springer Lecture Notes in Computer Science (LNCS, http://www.springer.com/gp/computer-science/lncs ) series and indexed by Scopus, EI Engineering Index, Thomson Reuters Conference Proceedings Citation Index (included in ISI Web of Science), and several other indexing services. The papers will contain linked references, XML versions and citable DOI numbers. Submitted papers will be subject to stringent peer review by at least three experts and carefully evaluated based on originality, significance, technical soundness, and clarity of exposition.
The authors can submit abstracts and papers to your session accessing the electronic submission site: http://ess.iccsa.org/ You can find the instructions to prepare and submit papers on the web site: http://www.iccsa.org/instructions-for-authors
If you are not registered, you must to register before the submission. From the personal page the author is able to submit first an abstract (phase 1), then a full paper (phase 2), selecting the session from the list of sessions in the submission forms.
The author will be able to update the paper until the submission deadline.
April 30, 2021: Deadline for abstract and paper submission to the CAS Workshop.
May 30, 2021: Notification of Acceptance
June 20, 2021: Early-bird Registration ends
June 20, 2021: Submission deadline for the final version of the Proceeding Papers
New Date (will be announced soon): ICCSA 2021 Conference.
SSA Vic is proud to present this workshop.
This two day workshop aims to enable R users and other data scientists to incrementally incorporate Julia in their workflow. After an introduction of Julia basics, the workshop focuses on the creation of a simple, yet computationally demanding simulation example. This Julia code is then incorporated in R and Python, illustrating how users may create new performant statistical software using Julia while maintaining existing code base in R or Python. With this exploration, participants will learn not just how to use Julia, but also how to integrate Julia into their day to day statistical analysis which may involve R or Python legacy code.
There is a lot of material presented in this workshop, and different attendees will work at different paces. For this reason, we'll use the following schedule:
This workshop is targeted at people who have used a language like R or Python before. Julia has a growing number of statistical libraries. It is fast, easy to use, and open source. Julia aims to solve the two-language-problem (https://www.nature.com/articles/d41586-019-02310-3).
Our workshop is closely followed by the free, online, JuliaCon 2021 conference (https://juliacon.org/2021/). So, there’s a great opportunity to link up with the Julia community afterwards.
Presenter: Associate Professor Yoni Nazarathy from the School of Mathematics and Physics at The University of Queensland specialises in data science, probability and statistics. His specific research interests include scheduling, control, queueing theory, and machine learning. He has been at UQ for nearly a decade, teaching courses at UQ’s Masters of Data Science program and working on research. Prior to his previous academic positions in Melbourne and the Netherlands, he worked in the aerospace industry in Israel. In recent years, he has also been heavily involved with primary and secondary mathematics education and is the co-founder of an EdTech mathematics organisation called One on Epsilon. Also, he is the co-author of an introductory data science book: Statistics with Julia, and a co-creator of the Mathematical Engineering of Deep Learning website. Like many other mathematics and physics academics, he took great interest in epidemics at the start of COVID-19 and leads the Safe Blues program. He also has interests in application areas such as power systems, agriculture, and road traffic control.
Required knowledge: Participants should to have prior basic programming experience in a language such as R or Python. They also should have basic knowledge in statistics equivalent to 2 or 3 university courses. Desirable knowledge: Further statistical knowledge would be useful for gaining more insights from the examples presented.
Cancellation Policy: Cancellations received one week prior to the event 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.
SSA and Flinders University are proudly offering this 2 day course with Presenter Dr Oscar Perez-Concha, Centre for Big Data Research in Health, UNSW Sydney.
This workshop introduces the basics for understanding and using machine learning algorithms.
We will discuss the machine learning workflow, from clearly defining our research question to the rationale behind choosing different machine learning techniques for different scenarios, highlighting questions such as over-fitting/under-fitting, missing data, and interpretability. We will focus on the principles behind some of the most used supervised learning algorithms.
However, the detailed mathematics underlying these algorithms will not be discussed.Real healthcare scenarios using Python will be presented. Participants need not have prior exposure to Python.
Dr Oscar Perez-Concha is a health data scientist with over 15 years’ experience in machine learning and statistical modelling. Oscar currently works as a Lecturer at the Centre for Big Data Research in Health (CBDRH), UNSW Sydney. His research focuses on answering questions related to health and healthcare, using statistical and machine learning methods on large electronic health record datasets. This is to identify and explore outcomes for these patient groups, improve patient care and streamline clinical processes. Oscar is also passionate about teaching and supervising students. In 2018, he developed an introductory course to Machine Learning which he convenes and teaches as part of the UNSW Master of Science in Health Data Science, the first such program in the southern hemisphere.
Day 1 - Morning
-Introduction to Artificial Intelligence and Machine Learning
-Basic principles of Machine Learning
Day 1 - Afternoon
-Machine Learning algorithms I: Lasso, Ridge, K-Nearest Neighbours
Day 2 - Morning
-Machine Learning algorithms II: Single Decision Trees, Random Forest, and Gradient Boosted Trees
Day 2 - Afternoon
-Machine Learning algorithms III: Introduction to Neural Networks and Deep Learning
Undergraduate-level statistics; Python knowledge would be beneficial but not essential.
You will be required to bring your laptop with a recent version of Anaconda installed. This software can be downloaded here.
On the day Coffee/tea will be offered on arrival, as well as Morning and Afternoon tea. Lunch is not provided.
Any questions contact email@example.com.
The address for the workshop is:
Flinders at Victoria Square, Level 1 Room 2, 182 Victoria Square, Adelaide 5000. (the old Reserve Bank Building).
Please enter from Flinders Street or Victoria Square.
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.
Cancellations received prior to Thursday, 28 June 2021 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.
Deadline for canceling the course based on number of registrations will be Monday 10th May 2021.
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.
Follow us on Twitter / Facebook / Instagram!
International Statistical Institute
2021 AMSI WINTER SCHOOL ON STATISTICAL DATA SCIENCE
APPLICATIONS ARE NOW OPEN FOR THE 2021 AMSI WINTER SCHOOL
AMSI and QUT are proud to present the 2021 Winter School on Statistical Data Science from 12-23 July.
For the first time, the program will be hosted virtually with options for students to attend event hubs in selected states. Boasting an impressive speaker line-up, attendees can delve deeper into modules focusing on Bayesian statistics, modern neural networks, and advanced Markov chains and Monte Carlo methods.
This event is aimed at postgraduate students, early career researchers and industry professionals wanting to sharpen their skills.
Program details are here below:
Event: AMSI Winter School 2021
Dates: 12 – 23 July
Where: Virtual program, with selected event hubs for those who wish to meet face-to-face
Theme: Statistical Data Science, featuring modules on:
Applications are now open and will close at 11.59pm on Sunday 20 June.
Scholarships are also available to AMSI Member students requiring financial assistance to cover program fees. To apply, go to https://ws.amsi.org.au/apply-for-a-scholarship/
For any further enquiries, please contact firstname.lastname@example.org
All students and early career biostatisticians, (i.e. within 10 years of completing biostatistics training) are invited to submit an abstract for an oral presentation at the ISCB Early Career Biostatisticians day on Thursday 22 July 2021. Presentations will be delivered online.
We are seeking oral presentations related to student, academic, research and professional life that are outside the scope of the main conference. This year we will have a special focus on the ethical challenges presented to biostatisticians and invite submissions relating to specific examples of ethical dilemmas in student and professional life. However, we welcome submissions on a range of themes such as choice of workplace, professional advancement, navigating professional relationships, and work-life balance.
To submit an abstract, visit.
Further information and key dates, click here.
AMSI-SSA PUBLIC LECTURE - DATA DETECTIVES ON THE TRAIL OF BLACK HOLE MERGERS Presented by Professor Renate Meyer, The University of Auckland and hosted as part of the 2021 AMSI Winter School on Statistical Data Science.
It has now been two decades since Bayesian parameter estimation methods were first introduced for studies in gravitational wave astronomy. Bayesian statistical approaches have become extremely important; their use is ubiquitous and helped to significantly advance our knowledge of the universe and its history. On 14 September 2015, Advanced LIGO made the breakthrough of the first detection of gravitational waves — ripples in the fabric of space-time caused by accelerating massive objects.
She will review how Bayesian computational methods helped to make sense of the data from the very first detection and from the subsequent observation runs of LIGO/Virgo and provide an outlook to the future space-based observatory LISA.
About Professor Renate Meyer, The University of Auckland
Renate is Professor of Statistics at the University of Auckland. After obtaining an MSc and PhD in Mathematics and Statistics from the University of Aachen, Germany, she took up a lectureship at the University of Auckland in 1994. In 2010, 2017, and 2018, she held visiting professorships at the Karlsruhe Institute of Technology, the Otto-von-Guericke University Magdeburg in Germany, and the Observatoire de la Côte d’Azur in France. She was awarded a James Cook Research Fellowship by the Royal Society of NZ in 2018 for research on noise characterization studies for laser-interferometric gravitational wave observatories and the Littlejohn Research Award of the NZ Statistical Society in 2020.
Renate has wide research interests in applied Bayesian inference, in particular time series analysis with applications in astrophysics, state-space modelling in ecology, multivariate modelling using copulas, survival analysis in medical statistics, and stochastic volatility models for financial time series.
To register, please click here.
First workshop at the ECSSC 2021.
Optimization plays an important role in fitting many statistical models. Some examples include least squares, ridge and lasso regression, Huber regression, and support vector machines. CVXR is an R package that provides an object-oriented modeling language for convex optimization. It allows the user to formulate convex optimization problems in a natural mathematical syntax rather than the standard form required by most solvers. Moreover, problems can be easily modified and re-solved, making the package ideal for prototyping new statistical methods. First, the user specifies an objective and set of constraints by combining constants, variables, and parameters using a library of functions with known mathematical properties. CVXR then applies disciplined convex programming (DCP) to verify the problem's convexity. Once verified, the problem is automatically converted into quadratic or conic form and passed to a solver like OSQP, MOSEK, or GUROBI. We demonstrate CVXR's modeling framework with several applications in statistics and machine learning.
We will begin with a gentle introduction to convex optimization using examples from ordinary least squares and penalized regression. This will be followed by a high-level description of CVXR, how it differs from other packages, and a discussion of the domain specific language that CVXR implements. We will show how CVXR works on different classes of problems, such as linear programs, quadratic programs, and semidefinite programs, and demonstrate its usage with a variety of examples. Finally, we will have a segment for potential developers in which we go over the nuts and bolts of adding new functions to CVXR’s library.
About the presenter: Anqi Fu is a Ph.D candidate in the Electrical Engineering department at Stanford University. Her research focuses on developing algorithms and software for large-scale optimization with applications to data science. One of her recent projects leverages methods from optimal control to design treatment plans for cancer radiation therapy. Prior to starting her Ph.D, Anqi worked as a machine learning scientist at H2O.ai. She received an M.S. in Statistics from Stanford University, and a B.S. in Electrical Engineering and a B.A. in Economics from the University of Maryland, College Park.
Prerequisites: A working knowledge of statistics and linear algebra, and basic experience with a scripting language like R. We also invite attendees to bring problems of interest, which we will do our best to formulate and solve in CVXR.
Prior to the course, please follow the instructions under “Preparatory Steps” at this link. At a minimum, you will need to install the latest stable version of R and CVXR.
Occasionally workshops have to be cancelled due to a lack of subscription. Early registration ensures that this will not happen.
Cancellation Policy: Cancellations received one week prior to the event will be refunded, minus a $20 administration fee. From then on-wards no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to email@example.com.
About the short course:
As modern data applications become complex in size and structure, identifying the underlying shape and structure has become of fundamental importance. The classical approaches such as dimension reduction are challenging for handling these applications. Topological data analysis (TDA) is a rapidly developing collection of methods that focuses on the “shape” of data. TDA can uncover the underlying low-dimensional geometric and topological structures from high-dimensional datasets. TDA has been successfully applied to various areas, including biology, network data, material science, and geology, in recent years. The goal of the lecture is to introduce novel TDA methods that can capture geometric or topological information of data and make statistical inferences. This lecture aims to familiarize these new methods along with their applications to various types of data.
About the presenter:
Chul Moon received his Ph.D. in Statistics from the University of Georgia. He joined the Department of Statistical Science at Southern Methodist University as an Assistant Professor in 2018. His research interests include topological data analysis, empirical likelihood, and ranked set sampling. His research aims to develop statistical methods in biosciences and geosciences.
Basic statistical knowledge and R
The Early Bird Deadline ends on 26 June 2021.
Source of figure: Ghrist, Robert. "Barcodes: the persistent topology of data." Bulletin of the American Mathematical Society 45.1 (2008): 61-75.
The Early Career & Student Statisticians Conference (ECSSC) 2021 will be held on 26 July to 1 August 2021. We are delighted to announce that we will be holding our conference virtually! ECSSC2021 will bring together the best students and early-career professionals in statistics and data analysis from all around Australia. This event is not to be missed!
To keep up-to-date with ECSSC2021, please go to the official conference website.
When you register for the conference, you need to be logged in as a member of SSA to take advantage of the member discount. Please note that a one-year student membership with SSA is available to full-time students for only $20! Click here to register as a member of SSA and to see where your membership can take you!
The early bird deadline closes on 26 May 2021.
This year, we are also giving high school students, who may be interested in a career in statistics, the opportunity to join our online conference free of charge.
ECSSC2021 - The Rising Stars of Statistics