If you've been worrying about how to combine the imminent Olympic fever with that other great passion — maths — then salvation is about to arrive. John D Barrow, eminent cosmologist, best selling author and director of the Millennium Mathematics Project (of which Plus is a part), has written a book, 100 essential things you didn't know you didn't know about sport, exploring the maths behind your favourite disciplines. And if you're near London or Cambridge you can see Barrow himself talk about some of its contents — for free!
Today is International Women's Day! Plus is run entirely by women who are happily disregarding maths and gender stereotypes, so we're very pleased to join in the celebrations. We've got lots of content by or about women mathematicians on Plus and here are some of our favourites. (And we'd like to ask all remaining dinosaurs to stop sending us emails starting "Dear Sirs"...)
Data, data, data — 21st century life provides tons of it. It's paradise for researchers, or at least it would be if we knew how to make sense of it all. This year's AAAS annual meeting in Vancouver
devoted plenty of time to the question of how to understand large amounts of data. And there's one method we
particularly liked. It's based on the kind of idea that gave us the London tube map.
Interested in the connections between art and science? Then come to this free public lecture at the Isaac Newton Institute in Cambridge on March 14, 2012 to hear theoretical physicist David Berman and artist Grenville Davey talk about string theory as an inspiration to art.
Struggling with that new year's resolution to lose a few pounds? Weight not dropping off as fast as you'd expected? A new mathematical model has some good news and some bad news for you. Which would you like to hear first?
How many people died? It's one of the first questions asked in a war or violent conflict, but it's one of the hardest to answer. In the chaos of war many deaths go unrecorded and all sides have an interest in distorting the figures. The best we can do is come up with estimates, but the trouble is that different statistical methods for doing this can produce vastly different results . So how do we know how different methods compare?