William Guy Lecturers 2024-25
The theme for the coming academic year (1 August 2024–31 July 2025) is Statistics in plain sight.
The lecturers will be aiming to inspire the next generation about the importance of statistics and data to the world around us – where the role of statistics is crucial but may not be immediately apparent. The talks will encourage young people to dig deeper and be curious about the building blocks behind their everyday activities and the topics they encounter in daily life. Read our blog about the theme.
Find out more about the 2024-25 lecturers and their talks below. Lecturers will be contactable from 1 August and their talks will be available on this page ahead of the start of the academic year.
- Mary Gregory, Interim Director of Population Statistics, Office for National Statistics, London, William Guy Lecturer for ages 5–11 – From sweets to streets: Understanding the world through statistics
- Nicola Rennie, Lecturer in Health Data Science, Lancaster University, William Guy Lecturer for ages 11–6 – From lab to patient: how statistics shapes decisions in medical treatment
- Mike Campbell, Emeritus Professor of Medical Statistics, University of Sheffield, William Guy Lecturer for age 16+ – Can I really believe that number? Statistics and Covid-19
Mary Gregory – William Guy Lecturer for ages 5–11
About Mary
Mary is a statistician at the Office for National Statistics. She is currently working on population statistics, having worked in different areas of government during her career. The variety of roles and topics she has worked on – including household energy use and the London 2012 Olympic Games – has reinforced the importance of statistics in so many aspects of our lives. Mary has also worked on championing good use of statistics by government and building data capability within the civil service. She has a keen interest in making statistics accessible and enjoyable for all.
Mary’s talk: From sweets to streets: Understanding the world through statistics
Numbers can be found everywhere. This talk provides an opportunity to learn more about how statistics can help us understand the world around us, with a strong emphasis on making the examples fun, engaging and applicable to anyone.
Illustrated examples are provided throughout the talk, supplemented with ideas for practical activities and topics for class discussion. The talk can be watched in one go, or each section can be used to support learning and spark follow-up discussion separately.
The talk will start by looking at how we can organise information to help understand patterns and probability. This will help us answer questions like, how many sweets are in a packet? How many of my favourite sweet should I expect?
We’ll then think about how we can use statistics to help inform important decisions, like where to build a school and how big it needs to be.
Finally, we’ll look at how to be good users of statistics and data, using critical thinking to consider whether numbers we see quoted by others make sense!
Nicola Rennie – William Guy Lecturer for ages 11–6
About Nicola
Nicola is a lecturer in health data science at Lancaster University. Nicola carries out research using healthcare data, including applying statistical and machine learning models to routinely collected data. She is especially interested in visualising data and understanding how we can better communicate statistics to general audiences. Nicola is particularly keen to show young people the broad variety of careers that statistics can lead them to and has delivered multiple talks to school students about using data to make the world better. She is keen to support women and minorities in their data science and programming journeys and organises local meetups to develop skills.
Nicola’s talk: From lab to patient: how statistics shapes decisions in medical treatment
The decisions behind the medications we take are more complex than you might think. When we experience symptoms like a headache or earache, we might take over-the-counter medications or seek help from healthcare professionals. But have you ever wondered how they determine which medication to give you and how much? Before a treatment reaches your hands, many decisions are made regarding its safety and effectiveness. Statistics plays a key role in guiding these decisions.
This talk will explore how statistics helps us to make informed choices in healthcare and medicine. I’ll discuss how researchers use statistical analysis to decide how many people are required to test a treatment in a clinical trial, to decide who those people should be, and to decide which people are allocated to which treatment. We’ll also talk about different ways we can measure how effective each treatment is, and evaluate whether it might be effective and safe for people it wasn’t tested on.
In the talk, we’ll discuss concepts such as randomisation, control groups, and the difference between statistical and clinical significance in simple terms. You’ll see how these (sometimes complex) ideas stem from topics you might cover in school such as means, sample sizes, and correlations. This talk will highlight the role of statistics in helping healthcare professionals make decisions about treatments, dosages, and side effects. It will show how statistics helps us to make informed choices and understand the world around us better. By learning about statistics in medicine, we’ll see how useful statistics is in real life and how it impacts our health and well-being every day.
Mike Campbell – William Guy Lecturer for age 16+
About Mike
Mike is Emeritus Professor of Medical Statistics at the University of Sheffield. He has always found time for teaching amongst a busy schedule of research, collaboration and administration, since teaching keeps him grounded and he loves meeting young people. He is now retired but he tutors GCSE students in Maths online and face-to-face through Action Tutoring, He has also been a STEM ambassador talking to sixth formers about his experiences on NICE, the committee that decides whether the NHS can approve certain drugs and procedures. Outside work he enjoys singing and tennis.
Mike’s talk: Can I really believe that number? Statistics and Covid-19
I will explain how I got where I am today. I will then consider some unusual numbers given recently in the press and whether we can believe them or not. I will show you how you can ask sensible questions about numbers to help you decide if the numbers are believable. Before you accept a number, say to yourself “WHOA!”:
- Why am I being given this number?
- How was it calculated?
- Other data available that it can be compared with?
- Accuracy – how well is this number estimated?
Four years ago, I was invited to join the Government Public Data Advisory Group (PDAG). It was the group’s job to critique slides prepared by the Office of National Statistics (ONS) for the Cabinet Office. These slides were used by Professor Chris Whitty, the Government Chief Medical Officer in the regular evening television broadcasts to the country on the Covid-19 crisis. It was only when I joined this group that I appreciated how the data were gathered and presented.
The remainder of the talk will cover questions such as: how would you know how many cases of Covid-19 there were in the country? How do you know that people who died with respiratory symptoms had Covid-19? How many deaths might have been caused by Covid-19 only indirectly, for example because people were reluctant to go to hospital during lockdown?
For international comparisons, which are important to see whether the UK dealt with the epidemic well, the number of excess deaths per head of the population is used. Excess deaths are deaths from any cause over and above what might be ‘expected’ without the pandemic. Their big advantage is that they don’t require Covid-19 testing. Some countries even achieved negative excess deaths because lockdown meant people were not dying from, say, road accidents. I will consider excess deaths by different country to discover, after four years, where the UK came in the international ranking for coping with Covid-19. I will finish with some suspicious statistics on Covid-19 vaccination rates.