Triangle mosaic updated 25.4. (missing information added)
Ian Stewart, Emeritus Professor of Mathematics at Warwick, has devoted many years of his life to popular science writing covering anything from logic and geometry as well as beauty and mystery.
British-American Professor Keith Devlin, Director of the Stanford Mathematics Outreach Project, has spent his professional live educating the wider public. He comments: "The key to success in school math is to learn to think inside-the-box. In contrast, a key feature of mathematical thinking is thinking outside-the-box – a valuable ability in today’s world."
Books, Podcasts and Videos and discussions of 17 Equations that changed the World by Ian Stewart
Online course Introduction to Mathematical thinking by Keith Devlin offered by Stanford, enrollment through coursera, starts 27.4.2020.
The R project: a free and open sources language. It is a major tool for applied statistics and data science. RStudio is a convenient platform for running R. Many packages covering specific functionalities and domains have been contributed by R users around the world, downloadable at GitHub and CRAN for free.
Our undergraduate students will get an extensive introduction to R, but you can already use online resources now to get a first taste of statistical programming, in particular if you would like to try your hand in exploring some data sets (see below).
Intro to R: getting started and data visualisation
R in Action ebook by Robert Kabacoff
Video tutorial by Greg Martin with global health data examples
Other intellectual and cultural resources:
Mathematics and statistics have some overlap with philosophy. To name just a few questions: What is deduction? What is inference? What are the meanings of uncertainty and randomness? And how would you define probability? Is it subjective or objective? What is the relationship between models and reality?
Learning how to get unstuck in a difficult maths problem needs creativity which can be practiced in many ways.
Interpretations of probability
Data-driven research about the pandemic
Mathematicians, statisticians and data scientists around the world play a central role in the fight against the pandemic, often in interdisciplinary projects. A major contribution to the research about the outbreak is monitoring and modelling of cases, hospitalisations, deaths and recoveries.
You can start exploring the development of about the pandemic yourself using publicly accessible datasets. Here are some repositories:
- The Real Time Epidemic Datathon organised by ETH Zürich provides a basic collection of world-wide and country-specific data sets.
- Covid-19 data set clearinghouse by UCLA covers data on outbreak as well as societal, mobility, medical and other information.
- Daily cases and deaths worldwide in one excel sheet at European Centre of Disease Prevention and Control (ECDP).
Finding good visualisations of the information contained in the raw data sets is a big challenge. Why not acquiring some basic R skills using the links above and trying your hand on some of the datasets?
Here are some examples of data visualisation and basic analyses that researchers have created and shared online: