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Puzzles
Triangle mosaicLink opens in a new window updated 25.4. (missing information added)
Recources
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Mathematical thinking: Ian StewartLink opens in a new window, 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 DevlinLink opens in a new window, 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." |
BooksLink opens in a new window, Podcasts and VideosLink opens in a new window and discussions of 17 Equations that changed the World Link opens in a new windowby Ian Stewart Online course Introduction to Mathematical thinkingLink opens in a new window by Keith Devlin offered by Stanford, enrollment through courseraLink opens in a new window, starts 27.4.2020. |
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Statistical programming: The R projectLink opens in a new window: a free and open sources language. It is a major tool for applied statistics and data science. RStudioLink opens in a new window 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 GitHubLink opens in a new window and CRANLink opens in a new window 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).
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Intro to R: getting started and data visualisationLink opens in a new window R in Action ebook by Robert KabacoffLink opens in a new window Video tutorial by Greg Martin with global health data examplesLink opens in a new window Learning R with RStudioLink opens in a new window Video tutorial by freeCodeCamp.orgLink opens in a new window |
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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. |
Philosophy Now podcastsLink opens in a new window Interpretations of probabilityLink opens in a new window British LibraryLink opens in a new window National Theatre at homeLink opens in a new window |
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 DatathonLink opens in a new window organised by ETH Zürich provides a basic collection of world-wide and country-specific data sets.
- Covid-19 data set clearinghouseLink opens in a new window 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).Link opens in a new window
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: