Inspiring tomorrow’s female mathematicians

Thursday 12th March 2020

Lancaster University Management School welcomed 136 pupils and 24 teachers from 14 schools and colleges in the North West on Thursday 9 January 2020 for the eighth annual Florence Nightingale Day. This is an enrichment event for female mathematicians in Years 11, 12 and 13, jointly hosted by Lancaster's Department of Mathematics and Statistics, Lancaster's Department of Management Science and the AMSP.

Florence Nightingale (1820-1910) is perhaps the most famous female statistician of all time, noted in particular for her work on visualising statistical data. Her polar area diagrams, or coxcombs, are renowned for showing the mortality figures during the Crimean War in an accessible format. She also had a longstanding career as a nurse. The year 2020 is the bicentenary of Florence Nightingale's birth, and it was fitting that this year's Florence Nightingale Day was the best attended so far.

The event was a mixture of presentations and workshops by current female mathematicians and statisticians together with a fiendish quiz, which students worked on in their school groups, hoping to win the prize for highest score.

We welcomed Dr Anna-Lena Sachs from Lancaster's Department of Management Science, who guided us through the mathematics of food waste, Dr Marnie Low from Glasgow, who showcased how statisticians use data visualisation (a great choice of topic given Florence Nightingale's groundbreaking work in this field), and Dr Katie Chicot from the Open University, who introduced everyone to infinity.

Feedback was excellent from both students and teachers. The event wouldn't have been possible without generous financial support from both Lancaster University and the AMSP - but, if the event inspires just one of the girls present to consider a career in maths, statistics or operational research, we think that is a great return on our investment!

To view more information, please visit Lancaster University’s websiteOpens a new window.

By James Groves

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