Event report: RSS fellows take Hands-on Statistics activities to CPD workshop

Written by Web News Editor on . Posted in Features

On Saturday 8 June 2019, Dr Simon White (University of Cambridge) and Dr Laura Bonnett (University of Liverpool), ran a workshop at a CPD event for Maths Scholars on behalf of the Royal Statistical Society’s Education and Statistical Literacy Committee.  

The full-day event was organised for 39 current and 10 alumni Mathematics Teacher Training Scholars and included three workshops to provide inspiration for potential school classroom activities. It was supported by the Department for Education and sponsored by the Royal Statistical Society, the Institute for Mathematics and its Applications, the London Mathematical Society, Mathematics Education Innovation, Mathematical Association and the National STEM Centre. 

Post-16 statistics qualifications in Scotland – an update

Written by Nevil Hopley on . Posted in Features

Nevil Hopley, RSS e-teacher member and head of mathematics at George Watson’s College in Edinburgh, outlines the statistics qualifications now on offer in Scotland for secondary school students aged over 16 years.

Firstly, a short definition of the names given to some SQA exams: many Scottish students, aged 17-18 years, in their final year at Secondary School can sit exams called ‘Advanced Highers’ before heading to University. The year before that, they typically sit exams called ‘Highers’.

Debates prompted by our 2018 Stats of the Year

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At the end of 2018, the RSS released our annual 'Statistics of the Year'. This was the second year of this exercise, to outline statistics from the year which we thought somehow captured the spirit of the year or told an overlooked story. Anyone can nominate a statistic to us, and our judging panel pick the strongest entries. Our aim is to engage the public with statistics, and it has largely been a successful exercise in generating public interest. 

One of our 'highly commended' statistics was 9.5 - which was the percentage point reduction in worldwide ‘absolute poverty’ during the ten year period, 2008-18 based on World Bank figures defining absolute poverty as below US$1.90 a day.

Event report: Poverty measurement seminar in Parliament

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On Tuesday 12 February 2019, the RSS staged a roundtable in Parliament on the new poverty measure developed recently by the Social Metrics Commission.

The keynote speakers were Baroness [Philippa] Stroud, Baroness [Ruth] Lister and Lord [David] Lipsey. It was chaired by Sir Peter Bottomley MP. The discussion centred around how the SMC’s new poverty measure might be adopted by government.

Event report: Early Career Researchers conference 2019

Written by Sarah Nevitt on . Posted in Features

The University of Liverpool was the host of the inaugural Early Career Researchers Conference 2019 bringing together early career researchers in Data Science, Machine Learning and Artificial Intelligence.

The Royal Statistical Society (RSS) were sponsors of the conference, and three Liverpool based volunteers who are active volunteers with the RSS, as well as statistical and STEM ambassadors coordinated a special afternoon showcasing the RSS and ‘Hands on Statistics’ outreach activities.

An interview with our president Deborah Ashby

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Professor Deborah Ashby is the new RSS President, a position she will hold until the end of 2020. We caught up with Deborah to find out more about her statistical background, her career in medical statistics and what she sees as the key issues in statistics over her forthcoming term as president.

From statistics graduate to medical statistician

My four-month sabbatical at AIMS Rwanda: part two

Written by Web News Editor on . Posted in Features

Marc Deisenroth travelled to Rwanda to teach statistics at the African Institute for Mathematical Sciences.

In the second installment of a two-part series, he talks about the masters course in Machine Intelligence that he taught, his experiences in teaching it, and his reflections more generally as his four-month sabbatical comes to an end. 


Teaching experience

During my time at AIMS, I taught a course on Foundations of Machine Learning, as part of the AMMI degree. The course covered mathematical foundations of machine learning and their application to (fairly basic) machine learning algorithms, such as linear regression or principal component analysis. The objective of this course was to uncover the intrinsic mathematical principles, which are often hidden in machine learning algorithms, to allow students to understand how and why these algorithms work and what their underlying assumptions are.

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