We are glad to announce that the 2018 Applied Bayesian Statistics Summer School (15th
edition) will be held in the magnificent Villa del Grumello, Como (Italy) along the Lake
Como shore.
BAYESIAN STATISTICAL MODELLING AND ANALYSIS IN SPORT
4-8 June, 2018
Lecturer: Kerrie MENGERSEN, Distinguished Professor of Statistics, Queensland University of Technology, Brisbane, Australia.
Further details are provided below.
Guido Consonni and Fabrizio Ruggeri ABS18 Directors Raffaele Argiento ABS18 Executive Director
------------------------------------------------------------------------
******************************* * ABS18 * *******************************
Applied Bayesian Statistics School
BAYESIAN STATISTICAL MODELLING AND ANALYSIS IN SPORT
Villa del Grumello, Como, Italy
4-8 June, 2018
Lecturer: Kerrie MENGERSEN, Distinguished Professor of Statistics, Queensland University of Technology, Brisbane, Australia.
The conference webpage is
web.mi.imati.cnr.it/conferences/abs18.html <<<<
Registration is now open. Please note that the conference room allows only for a limited number of participants.
The ABS18 Secretariat can be contacted at
fabrizio@mi.imati.cnr.it
COURSE OUTLINE
The aim of this course is to increase students' ability to develop Bayesian models and
computational solutions for real problems in the world of sport. A case study based teaching
approach will be taken for the course. Each day, students will be presented with one or two
problems posed by Sports Institutes regarding aspects of athlete training for world games.
Through participatory problem solving, the students will be challenged to learn about
theory, methods and applications of a range of Bayesian models including mixtures, spatio-
temporal models, hidden Markov models and experimental design, and computational approaches
including Markov chain Monte Carlo and Approximate Bayesian Computation. This hands-on
course pays equivalent attention to theory and application, foundation and frontiers in
Bayesian modelling and analysis. While the focus of the case studies is on sport, both
sporting novices and lovers of sports are welcome, noting that the learning obtained in the
course will be widely applicable to many other areas.
COURSE SCHEDULE
Day 1: Lectures on introduction to Bayesian modelling and computation. Presentation of
Problem 1: ranking and benchmarking athletes. Discussion and implementation of potential
Bayesian hierarchical models and computational solutions. Communication of results.
Day 2: Lectures on foundational Bayesian theory. Presentation of Problem 3: modelling
swimmers' effective work per stroke. Discussion and implementation of potential Bayesian
high dimensional regression models and computational solutions. Communication of results.
Presentation of Problem 4: modelling cyclists' wearable data. Discussion and implementation
of potential (marked) time series models and computational solutions. Communication of
results.
Day 3: Lectures on foundational Bayesian computation. Presentation of Problem 5: optimising
athletes' resilience. Discussion and implementation of potential Bayesian mixture models to
relate performance, fatigue and recovery. Communication of results.
Day 4: Lectures on foundational Bayesian computation and frontier Bayesian theory.
Presentation of Problem 6: optimal sampling strategies. Discussion and implementation of
potential Bayesian experimental design methods for acquiring data from athletes.
Presentation of Problem 7: using video data to compare planned and set play in team sports.
Discussion and implementation of potential Bayesian spatio-temporal models. Communication of
results.
Day 5: Lectures on frontier Bayesian computation. Finalisation of problems 1-7. Extensions.
Concluding remarks.
PRACTICAL INFORMATION
The school will replicate the successful format of the previous years, and will feature
lectures and practical sessions (run by a junior researcher), as well as participants'
talks. It will start on Monday after lunch and end on Friday before lunch; Wednesday
afternoon is free. Accommodation is available either at the Villa guesthouse or in downtown
hotels (info will appear soon on the website). Como can be easily reached by train from
Milan and its airports. More details are available on the website.
We are glad to announce that the 2018 Applied Bayesian Statistics Summer School (15th edition)
will be held in the magnificent Villa del Grumello, Como (Italy) along the Lake Como shore.
BAYESIAN STATISTICAL MODELLING AND ANALYSIS IN SPORT
4-8 June, 2018
Lecturer: Kerrie MENGERSEN, Distinguished Professor of Statistics, Queensland University of Technology, Brisbane, Australia.
Further details are provided below.
Guido Consonni and Fabrizio Ruggeri ABS18 Directors Raffaele Argiento ABS18 Executive Director
------------------------------------------------------------------------
******************************* * ABS18 * *******************************
Applied Bayesian Statistics School
BAYESIAN STATISTICAL MODELLING AND ANALYSIS IN SPORT
Villa del Grumello, Como, Italy
4-8 June, 2018
Lecturer: Kerrie MENGERSEN, Distinguished Professor of Statistics, Queensland University of Technology, Brisbane, Australia.
The conference webpage is
web.mi.imati.cnr.it/conferences/abs18.html <<<<
Registration is now open. Please note that the conference room allows only for a limited number of participants.
The ABS18 Secretariat can be contacted at
fabrizio@mi.imati.cnr.it
COURSE OUTLINE
The aim of this course is to increase students' ability to develop Bayesian models and
computational solutions for real problems in the world of sport. A case study based teaching
approach will be taken for the course. Each day, students will be presented with one or two
problems posed by Sports Institutes regarding aspects of athlete training for world games.
Through participatory problem solving, the students will be challenged to learn about
theory, methods and applications of a range of Bayesian models including mixtures, spatio-
temporal models, hidden Markov models and experimental design, and computational approaches
including Markov chain Monte Carlo and Approximate Bayesian Computation. This hands-on
course pays equivalent attention to theory and application, foundation and frontiers in
Bayesian modelling and analysis. While the focus of the case studies is on sport, both
sporting novices and lovers of sports are welcome, noting that the learning obtained in the
course will be widely applicable to many other areas.
COURSE SCHEDULE
Day 1: Lectures on introduction to Bayesian modelling and computation. Presentation of
Problem 1: ranking and benchmarking athletes. Discussion and implementation of potential
Bayesian hierarchical models and computational solutions. Communication of results.
Day 2: Lectures on foundational Bayesian theory. Presentation of Problem 3: modelling
swimmers' effective work per stroke. Discussion and implementation of potential Bayesian
high dimensional regression models and computational solutions. Communication of results.
Presentation of Problem 4: modelling cyclists' wearable data. Discussion and implementation
of potential (marked) time series models and computational solutions. Communication of
results.
Day 3: Lectures on foundational Bayesian computation. Presentation of Problem 5: optimising
athletes' resilience. Discussion and implementation of potential Bayesian mixture models to
relate performance, fatigue and recovery. Communication of results.
Day 4: Lectures on foundational Bayesian computation and frontier Bayesian theory.
Presentation of Problem 6: optimal sampling strategies. Discussion and implementation of
potential Bayesian experimental design methods for acquiring data from athletes.
Presentation of Problem 7: using video data to compare planned and set play in team sports.
Discussion and implementation of potential Bayesian spatio-temporal models. Communication of
results.
Day 5: Lectures on frontier Bayesian computation. Finalisation of problems 1-7. Extensions.
Concluding remarks.
PRACTICAL INFORMATION
The school will replicate the successful format of the previous years, and will feature
lectures and practical sessions (run by a junior researcher), as well as participants'
talks. It will start on Monday after lunch and end on Friday before lunch; Wednesday
afternoon is free. Accommodation is available either at the Villa guesthouse or in downtown
hotels (info will appear soon on the website). Como can be easily reached by train from
Milan and its airports. More details are available on the website.
-
Consonni Guido