Piotr Fryzlewicz on why choose statistics

April is Mathematics and Statistics Awareness Month, a timely opportunity to help raise the awareness and understanding of the field.

To aid this quest, a number of renowned Wiley Editors, Editorial Board Members and Authors have taken the time to tell us why they embarked on their journey in their chosen fields, what inspires and excites them, and why they’d encourage you to take the plunge!

This month The Wiley Network will publish some selected responses for you to read and share with your colleagues, students and friends. All responses will feature on StatisticsViews.com throughout April.

In continuing our series, Professor Piotr Fryzlewicz, Professor of Statistics at the London School of Economics shares his story.


1. How or why did you choose statistics as a career path/study area?

The curriculum in my MSci degree programme in mathematics at Wroclaw University of Technology (Poland) was packed with measure-theoretic probability, in keeping with the good Polish tradition in this field. Probability as a discipline appealed to me immediately, mainly because I felt it provided a neat and self-contained way of describing real-life uncertainty. From there, progression to statistics was fairly natural: I saw statistics as a platform for solving problems and making decisions in a probabilistic way, which I thought reflected well the non-deterministic nature of the world.

But I did not make this career choice in isolation – I was very lucky to have great teachers and mentors (such as Malgorzata and Krzysztof Bogdan, Czeslaw Ryll-Nardzewski, Guy Nason, Bernard Silverman, Peter Green and many more) who gave me enough inspiration for probability and statistics to last me at least until now!

2. What inspires you about statistics?

What I find the most inspiring is the number and variety of fields and domains that have adopted statistics (and the broader data science) as their preferred “language”: medicine, bioinformatics, computer vision, commerce, finance, economics, geosciences – the list is endless. It will also only ever get longer, as humans (and machines!) measure more and more things. From this point of view, it is probably safe to say that statistics as a way of thinking is “future-proof”, which is another thing that inspires me.

From a different and a more specific perspective, I should also mention one particular website I have found extremely inspirational, and that is www.gapminder.org, founded by Hans Rosling. I find its mission, to debunk misconceptions about the world using data, absolutely fascinating, and a perfect antidote to today’s “fake news”, biased figures quoted by politicians, etc. We need many more gapminders.

“…it is probably safe to say that statistics as a way of thinking is “future-proof”…”

3. What’s been the most exciting thing about your career in statistics?

Having been able to work on some fascinating problems and with some exciting datasets, either solo or with smart and insightful colleagues and students. Knowing that my research may have made some difference – either to the companies for which I have served as a consultant, or to the authors who have used and cited my work. Teaching students about best practices in modern statistics and data science.

4. What would you say to students/Early Career Researchers who may be considering statistics as a study option/career choice?

Don’t look any further – statistics is a great field to be in. As a statistician, you will be able to make a difference by solving important complex problems and making principled quantitative statements about the world. Your occupation will be a “creative” one in the sense that your task will be to “create” knowledge from data (a cliché, but one that is certainly true). With the ongoing “quantification” of the world, your skills will be in ever higher demand in countless fields of application. Still unconvinced? Visit www.kaggle.com and take part in some interesting data science competitions. This will also help you appreciate the breadth and power of modern statistics/data science, and the enormous demand for it.

Piotr Fryzlewicz obtained an MSci Mathematics degree from Wroclaw University of Technology, Poland (in 2000), and a PhD degree in statistics from the University of Bristol, UK (in 2003), where he wrote a thesis on “Wavelet techniques for time series and Poisson data” under the supervision of Guy Nason. He then worked at Imperial College, the University of Bristol and Winton Capital Management, before moving to the London School of Economics, where he has been Professor of Statistics since 2011. Piotr is a recipient of the Guy Medal in Bronze (2013) from the Royal Statistical Society, and currently holds a five-year Fellowship from the Engineering and Physical Sciences Research Council. He is a former Joint Editor of the Journal of the Royal Statistical Society Series B. His research interests are in multiscale modelling and estimation, time series, change-point detection, high-dimensional statistical inference and dimension reduction, statistical learning and networks.