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On Wednesday, July 2nd, we have two pre-conference courses available!
You can book them with the registration of a main conference ticket. Click the titles to read their abstracts.
Introduction to Joint Modelling
Wednesday 2nd am - Dr Maria Sudell
This course will focus on providing participants with a solid foundation in the principles and practical applications of joint modelling, emphasising its utility in analysing complex longitudinal and time-to-event data from multiple sources. Maria’s research, which explores improving the efficiency of multilevel models using computer science methods, ensures her teaching is at the cutting edge of methodological advancement. Delegates will leave her session equipped with essential skills and insights for employing joint modelling techniques effectively, making it a vital addition to the conference programme.
Stories, scripts & slides: a guide to giving a good presentation
Wednesday 2nd pm - Dr Laura Bonnett
This will be an exclusive three-hour session at our conference tailored specifically for statistical researchers. This dynamic workshop will equip participants with practical strategies to communicate their research effectively to diverse audiences, including policymakers, the public, and interdisciplinary peers. Combining their expertise in academia and performance, the presenter will provide hands-on training in crafting clear, compelling messages, enhancing presentation skills, and leveraging storytelling techniques to make complex ideas accessible and memorable. Attendees will leave with actionable tools to elevate their scientific outreach, fostering greater impact and engagement for their work.
We also have exciting plenary sessions lined up for the 3rd and 4th of July, featuring the following speakers:
Statistics and the law: what’s the verdict?
Dr Amy Wilson
Criminal cases can feature multiple pieces of dependent evidence and multiple possible explanations for this evidence. It can be challenging to disentangle the correlations between pieces of evidence and to understand how to form a logically consistent argument that accounts for this evidence in a way that is probabilistically sound. There have been high profile miscarriages of justice that have resulted from failures in probabilistic reasoning and interpretation.
In this talk I will show how chain event graphs can be used to construct possible storylines for displaying the time evolution of events and evidence in criminal cases. These chain event graphs can both be used to investigate possible arguments when drawing up a case and to make probabilistic assessments of the strength of evidence when prosecuting or defending. I will give two examples – a drugs on banknotes case and the case of the murder of Meredith Kercher. To finish the talk I will discuss the role that statistics and probabilistic reasoning can play in criminal cases, including in the recent Lucy Letby case, and highlight where greater collaboration is needed between statisticians and those in the legal sector.
When prediction meets causal inference
Prof Ruth Keogh
Common aims in health research are to predict the risk of an adverse outcome or estimate the causal effect of a medical intervention. The tasks of making predictions and investigating causal effects are often viewed as separate. However, tools traditionally used in prediction modelling are increasingly used to help to solve certain challenges in causal inference, and it has also been shown how causal concepts are important in the context of clinical prediction modelling. For example, prediction methods for estimating outcomes conditional on a set of covariates, including machine learning methods, are used to fit nuisance models which are ingredients to procedures for estimating causal effects. In the other direction, it is often of interest to use risk predictions to inform whether a person should initiate a particular treatment, but it has been underappreciated that this requires causal considerations and analysis tools. This talk will discuss what prediction can do for causal inference and vice versa.
Finding MH370
Prof Simon Maskell
MH370 went missing on 8 March 2014 with 239 people onboard, travelling for several hours after its ADS-B transponder stopped transmitting the aircraft’s position. Data from an Inmarsat satellite have been used by multiple teams to attempt to localise the aircraft’s position when it ran out of fuel. A novel methodology for processing data from amateur radio enthusiasts has also been claimed to provide pertinent information related to the trajectory taken by the aircraft. Simulations from Boeing have modelled the descent, with the Inmarsat data also providing information about the rate of descent. Data from the Comprehensive Nuclear-Test-Ban Treaty Organization’s sensors have been collected and, usefully, do not appear to include any acoustic signatures from the impact. Debris, perceived to be from MH370, has been found and oceanographic drift models have been used to infer where the debris has come from. The modulation of barnacle-growth by sea temperature has been postulated as providing information about the paths taken by the debris and so the location where the debris came from. Despite all this and a search that has covered over 200,000 km2 of the Indian Ocean’s sea-bed, MH370 remains to be found. None-the-less, following the 10 year anniversary in 2024, discussions with the Malaysian government have culminated in Ocean Infinity starting a new search. This talk will explain the signal processing involved in extracting pertinent information from these different data, discuss the role of interdisciplinary research in this endeavour and highlight the challenges in calculating the search area.
Impact, by Chance or by Choice: A Statistician’s Story
Dr David Hughes
Academics are always under pressure to demonstrate the impact of their work. But for statisticians, working as part of larger teams, this often feels harder to quantify. In this talk, I’ll be describing some of the statistical work I’ve been involved and discuss how the work of a statistician is both interesting and useful for the wider scientifice community. I’ll touch on some highs and lows in this statisticians quest for impact.
An Introduction to Sports Analytics
Dr Benjamin Holmes
Abstract TBC
Please note, the YSM organisers are not responsible for any changes to the schedule, venue, or line-up due to unforeseen circumstances.
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