Durham University Statistics and Probability Group
Durham University Statistics and Probability

Previous talks 2013/2014

Wednesday 19th March 2014:

Techniques of ancient - DNA analysis

Speaker: Liisa Loog, Department of Archaeology, Durham University

Abstract

The field of ancient DNA has grown tremendously in recent years. Although modern genetic data has been used for some time to make inferences about the past, ancient DNA is an invaluable new tool for archaeological research as it provides direct information about the genetic diversity of past populations. This new temporal dimension in the data also requires new analytical approaches, different from the classical ones commonly used to analyse modern genetic variation. In this seminar I am going to talk about some already existing approaches to accommodate time-stamped genetic variation data (computer simulation based approaches as well as recently created new summary statistics) along side with a new method that we developed for exploring migratory activity of past populations.

Extra Stats4Grads activity!

On Wednesday 12th March, our very own Frank Coolen and Louis Aslett from Oxford will hold a tutorial on "Bayesian inference for reliability of systems and networks using the survival signature." We decided to include this in our schedule as an extra Stats4Grads activity. This meeting will include a short presentation followed by discussion and the tutorial for "Bayesian inference" and is part of the Asset Management Work Group in Durham.

For more information please visit the Asset Management webpage.

The meeting will be held in CM105 (ground floor in Mathematical Sciences) at 13.00. Please feel free to come and let any one of interest know about it.

Wednesday 5th March 2014:

Applied Nonparametric Circular Methods

Speaker: Dr Maria Oliveira, Department of Mathematics, Statistics and Probability Group

Abstract

The goal of this talk is to introduce nonparametric methods for density and regression estimation for circular data, analyzing their performance through simulation studies and illustrating their use by real data applications. In addition, the R library NPCirc, which implements the proposed methods, will be presented.

Wednesday 19th February 2014:

Decision making under uncertainty

Speaker: Dr Nathan Huntley, Department of Mathematics, Statistics and Probability Group

Abstract

Whether we are policy-makers planning flood defences, or just customers trying to choose their preferred sandwich, we all have to make decisions with uncertain consequences. The theory of expected utility provides a popular and convenient method to deal with decision problems, but is it the right approach? In this talk I'll illustrate the theory, some criticisms and alleged paradoxes, and some possible alternatives.

Wednesday 5th February 2014:

Turning Lines into Numbers and Other Stories from an Archaeologist

Speaker: Michelle de Gruchy, Department of Archaeology

Abstract

A persistent challenge in archaeology is that often our data does not look like the data presented in statistical courses or textbooks. Half the battle is figuring out how to turn our data into meaningful values so that it is possible to have the means, standard deviations, and so on required in statistical tests. In my research, this has inventing a quantitative method for looking at archaeologically preserved routes by building populations from single samples and turning computer- or hand-drawn lines into numbers, in order to learn why people walked one way and not another thousands of years ago. This talk tells the story of how this quantiative method was invented and what it is starting to tell us about travel during the Early Third Millennium B.C.

Wednesday 22nd January 2014:

Uncertainty Analysis of Future Power Systems

Speaker: A. Lawson, Mathematical Sciences

Abstract

At the time investment decisions are made there is a lot of uncertainty in the future of Britain's power system. Full simulators are too expensive to be used in the face of uncertainty. Statistical emulators are therefore used to approximate simulators and make good investment decisions.

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