Mon 27 Feb – joint event with RSS Glasgow local group (livestreamed)

Statistics & The Law – an event hosted jointly by the RSS Statistics and Law section and the RSS Glasgow local group.

Date:                                    Monday 27th February 2017

Speakers:                            Professor Jane Hutton, Department of Statistics, University of Warwick; Dr Tereza Neocleous, School of Mathematics & Statistics, University of Glasgow

Time:                                    5.30pm-7pm (followed by drinks and nibbles)

Place:                                    LT 908, Livingstone Tower, University of Strathclyde, Glasgow, G1 1XH

Livestreaming:                  This event will be simultaneously broadcast online via livestream

Registration:                       Please register to attend the event in person or to join the livestream here: https://sites.google.com/site/rssglasgow/events Those who for the livestream will be contacted via email with a link and participation details 24 hours prior to the event

Twitter:                                Join the discussion and post questions using the hashtag  #RSSGlaLaw

Title/Abstracts:
Jane Hutton: Epidemiological evidence in civil legal cases – ‘If anticoagulants had been administered sooner, my client would not have died.’ ‘This drug damaged the sight of my patient.’ How much money should be awarded to a child who is disabled due to medical negligence? Should a teenager with cancer be given active treatment if doctors estimate he has two weeks to live? Statements and questions such as these are the basis of civil law suits, in which one party claims damages from a second party, or demands particular actions. Many lawyers still only request expert opinions from medical doctors. However, statisticians can contribute to civil law suits by finding evidence relevant to the particular case, evaluating it, and then presenting the information.

Tereza Neocleous: Models for forensic speaker comparison – This talk will present ways in which statistical modelling can be used to evaluate the evidential value of voice recordings such as those occurring in hoax phone calls, calls related to extortion, fraud cases, or involving abuse or threats. Examples of how vocal features extracted from such recordings can be modelled to provide a measure of the strength of evidence will be presented, followed by a discussion of opportunities and challenges in this field in the era of big data.