Access to Data Science: start your PhD journey with Compass

Posted on by crina.radu

Want to find out what a modern PhD in Statistics and Data Science is like?

Access to Data Science provides an immersive experience for prospective PhD students. This fully-funded, two-day event will be hosted by Compass academics and PhD students in the Fry Building, home to the School of Mathematics at the University of Bristol.

Application deadline: Monday 18 October 2021

Event dates: Monday 8 November – Tuesday 9 November

Find out more about the event here

The purpose of this event is to increase all aspects of diversity amongst data science researchers. We particularly encourage applications from women and members of the LGBTQ+ and BAME communities to join us. 

             

What to expect from the Access to Data Science event:

  • attend seminars and guest lectures
  • take part in a hands-on workshop
  • have exclusive access to an application writing workshop
  • work with the current Compass PhD students
  • option to attend the Women and non-binary people in mathematics event.

Who can attend

We welcome participants from a range of numerate academic backgrounds, with undergraduate degrees in subjects such as computer science, economics, epidemiology, mathematics, statistics and physics.

We welcome applications from across the UK. Access to Data Science participants will be offered hotel accommodation, reimbursement of travel costs and meals for each day of the event.

Apply to Access to Data Science here 

Compass Away Day

Posted on by crina.radu

At the end of July 2021, Compass students and staff travelled together to the Brecon Beacons National Park in Wales for a day full of adventure, which was carefully planned by Call of the Wild.

 

 

 

 

 

Activities on the day started with some fun team tasks called the ‘Mini Olympics’. Some of the tasks tested logical thinking, the ability to do a task under time pressure, or simply work as a team to complete a certain objective but ultimately to have fun and a laugh.

 

The tasks were a great opportunity to work together and get to know each other better. Some of them have been more difficult to complete than our students and staff initially expected, but very enjoyable.

 

 

After lunch Compass students and staff started a 3-hour Canyoning adventure, guided by the very well trained Call of the Wild team.

The best way of describing this canyoning activity is white water rafting but without the raft. With qualified guides, our students and staff descended a stunning steep sided gorge by various ways and means. This involved sliding down rapids, swimming down rapids, floating down fast flowing chutes and waves, walking behind some breathtaking waterfalls and of course jumping off some jaw dropping waterfalls.

 

 

After this thrilling adventure, Compass students and staff travelled to the Vale Resort where they enjoyed dinner together and leisure time until the day after when it was time to come back to Bristol.

It was wonderful to be able to spend time together after the long months of working from home.

 

 

 

 

 

 

 

Student Perspectives: Contemporary Ideas in Statistical Philosophy

Posted on by az15360

A post by Alessio Zakaria, PhD student on the Compass programme.

Introduction

Probability theory is a branch of mathematics centred around the abstract manipulation and quantification of uncertainty and variability. It forms a basic unit of the theory and practice of statistics, enabling us to tame the complex nature of observable phenomena into meaningful information. It is through this reliance that the debate over the true (or more correct) underlying nature of probability theory has profound effects on how statisticians do their work. The current opposing sides of the debate in question are the Frequentists and the Bayesians. Frequentists believe that probability is intrinsically linked to the numeric regularity with which events occur, i.e. their frequency. Bayesians, however, believe that probability is an expression of someones degree of belief or confidence in a certain claim. In everyday parlance we use both of these concepts interchangeably: I estimate one in five of people have Covid; I was 50% confident that the football was coming home. It should be noted that the latter of the two is not a repeatable event per se. We cannot roll back time to check what the repeatable sequence would result in.

(more…)

Student perspectives: How can we do data science without all of our data?

Posted on by Daniel Williams

A post by Daniel Williams, Compass PhD student.

Imagine that you are employed by Chicago’s city council, and are tasked with estimating where the mean locations of reported crimes are in the city. The data that you are given only goes up to the city’s borders, even though crime does not suddenly stop beyond this artificial boundary. As a data scientist, how would you estimate these centres within the city? Your measurements are obscured past a very complex border, so regular methods such as maximum likelihood would not be appropriate.

Chicago Homicides
Figure 1: Homicides in the city of Chicago in 2008. Left: locations of each homicide. Right: a density estimate of the same crimes, highlighting where the ‘hotspots’ are.

This is an example of a more general problem in statistics named truncated probability density estimation. How do we estimate the parameters of a statistical model when data are not fully observed, and are cut off by some artificial boundary? (more…)

Compass is funded by EPSRC
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