**The Centre for Mathematical Sciences**** research seminars and events are listed below.**

The four main seminar series are in applied mathematics, pure mathematics, statistics and theoretical physics. Visit the centre's webpages for the latest seminar updates and information.

**Thursday 5 - Friday 6 September | Room 204, Rolle Building**

**Water Waves - Mathematical Theory and Applications**

1.5 day workshop on theoretical and applied aspects of water waves. Speakers: David Andrade (Technion); Ton van den Bremer (Oxford); Anna Kalogirou (Nottingham); Dan Liberzon (Technion); Kateryna Marynets (Vienna); Emilian Parau (UEA); Alison Raby (Plymouth); Raphael Stuhlmeier (Plymouth).

Funded by a Celebrating New Appointments Grant from the London Mathematical Society. Visit the event webpage for full details or contact raphael.stuhlmeier@plymouth.ac.uk for any queries.

**Wednesday 25 September | Room 101, Rolle Building (15:30-16:00)**

**Statistics in Wellbeing**

- Speaker: Lauren Stockley, University of Plymouth

Abstract: The Office for National Statistics use four subjective measures to understand wellbeing in the UK. The aim of the project was to gain a further understanding as to whether other, objective, factors influence a person’s well-being and if so, which of these are the most important.

Principal Components Analysis was used to combine the four wellbeing variables for subsequent analysis. A variety of different regression techniques for modelling the data were then considered, namely classical linear regression, quantile regression and Poisson regression. The combined wellbeing variable was used as the response variable and the remaining variables in the dataset were used to explain it. Various techniques were considered in the linear regression analysis to select the best subset of predictors to explain a person’s wellbeing. The chosen model was then interpreted to determine how each variable affects well-being using the three different regression models. All models considered found very similar results when comparing how each variable explains wellbeing. Cross-validation was used to measure the performance of the linear and Poisson models through prediction. The linear model was found to produce well-being predictions closer to the true values than the Poisson model when evaluating the models using mean squared error.

A non-parametric model, random forest regression was fit to the data and used as a way of testing the importance of predictors in the model. This analysis showed that the most important variables for explaining wellbeing are disability, marital status and age of respondent.

Contact yinghui.wei@plymouth.ac.uk for any queries.

**Wednesday 25 September | Room 101, Rolle Building (16:00-17:30)**

**The Teaching Statistics Trust Lecture 2019: The purpose of statistics is insight not numbers**

- Speaker: Neil Sheldon

Abstract: In recent years, statistics teaching has seen a welcome move away from formulae and calculation. Especially with the rise of ‘big data’, numerical processing is increasingly being done with software, and it is becoming much more important for students to learn the art and science of interpretation. This development requires teachers to change focus too, shifting their emphasis from numbers to language.

As with many academic disciplines, statistics overlays everyday language with specialist meaning: one familiar example is the word ‘significant’ which means very different things in everyday use and in statistics. Research shows that parallel meanings such as this make it harder for students to understand technical concepts. Research also shows that teaching with a richer vocabulary can help to overcome this problem of understanding.

But statistics is more than just an academic discipline, it is a vital element of citizenship: we all need statistical understanding to make sense of the world around us. Yet statistical data are routinely misunderstood and misinterpreted in the media. In most cases the errors arise, not from the numbers themselves, but from the confused and inaccurate language used to comment on them. Clear language is essential to clear thought.

This lecture, drawing on numerous practical examples, will explore the ways in which careful use of language can help everyone – teachers, students and citizens – to understand statistics better, whether in formulating enquiries, interpreting data, or reaching trustworthy conclusions and communicating them effectively.

Neil Sheldon was a teacher for more than 40 years. He is a Chartered Statistician and a former Vice-President of the Royal Statistical Society. He was the RSS Guy Lecturer in 2007-8 and he is currently Chair of the Teaching Statistics Trust. Neil’s other academic interests include philosophy and linguistics.

The Teaching Statistics Trust Lecture is given annually at multiple locations. It is aimed at teachers of statistics, whether specialist or non-specialist, in secondary schools, colleges and early years of university.

Contact yinghui.wei@plymouth.ac.uk for any queries.

**Wednesday 30 October | Stonehouse Lecture Theatre, Portland Square Building**

**Pigeon-holes and mustard seeds: Growing capacity to use data for society**

- Speaker: Professor Deborah Ashby, Imperial College London

The Royal Statistical Society was founded to address social problems ‘through the collection and classification of facts’, leading to many developments in the collection of data, the development of methods for analysing them, and the development of statistics as a profession. Nearly 200 years later an explosion in computational power has led, in turn, to an explosion in data. We outline the challenges and the actions needed to exploit that data for the public good, and to address the step change in statistical skills and capacity development necessary to enable our vision of a world where data are at the heart of understanding and decision-making.

Contact yinghui.wei@plymouth.ac.uk for any queries.