Data Science: The View from the Mathematical Sciences
The 35th Fisher Memorial Lecture will be given by Professor Nancy Reid (University of Toronto) as a part of this half-day conference.
The full programme is as follows:
2pm Neil Lawrence and MIke Smith (Sheffield): Computational perspectives: Fairness and awareness in the analysis of data
What is data science? A new name for something old perhaps. Nevertheless there is something new happening. Data is being acquired in ways that could never have been envisaged 100 years ago. This is presenting new challenges, and ones that no single field is equipped to face. As well as the need for new methodologies and theoretical underpinnings, modern data processing is having a direct effect on our citizens in real time. In this talk I'll suggest that data science provides a banner under which the computational and statistical sciences can unite to provide an unified response.
2.45pm Johan Koskinen (Manchester): Generative and estimable models for longitudinal social networks
It could be argued that data are never independent (or iid) other than as an artefact of sampling procedures. People rarely act independently of other people and a particularly apt example of this is network data, where we observe ties among social units. These objects, and dynamic networks in particular, are typically highly complex and rarely amenable to standard statistical analysis. Yet we want to draw meaningful and consistent conclusions from these data. Snijders introduced a novel approach to analysing longitudinal social networks that was inspired by agent-based modelling and simulations of social processes. A set of stochastic rules are set up that guides actors in a network when they form and break off ties to other actors, allowing for modelling complex outcomes yet has statistical parameters that are estimable from data. Simulation is not only an inferential tool, all statistical models may be thought of as simulation models for social processes. Using the building blocks of the stochastic actor-oriented model we illustrate this principle by defining and estimating a model for moves on the housing market that is couched in the form of a social process. This is an exemplar of how data science is what results when we are willing to eschew disciplinary boundaries in tackling the understanding of complex data.
4pm The Fisher Lecture: Nancy Reid (Toronto): Statistical science and data science: where do we go from here?
Statistics departments in Canada are scrambling to introduce programs in data science, and the situation is doubtless very similar in many other countries. Many of these programs concentrate on training, with somewhat less emphasis on research. I will present my views on some of the associated research areas, with emphasis on lessons learned from a six-month thematic program on Big Data that took place at the Fields Institute in 2015. While it is difficult to predict the long term impact of the rush to data science, there does seem to be an interesting mix of both old and new statistics involved.
5.15pm Drinks and light refreshments
We are grateful to the London Mathematical Society for sponsoring lunch and the post-lecture refreshments
|Contact Register here: https://events.rss.org.uk/rss/55/register|
There no charge to attend but registration is required.
Organiser Name Paul Gentry
Organising Group(s) Royal Statistical Society, Fisher Memorial Trust and the London Mathematical Society