What would you like to know about your Universe — The third online poll
This poll is now closed. The most popular question was: "What are dark energy and dark matter?" We will publish the answer in an article and podcast on Plus shortly. Thank you for taking part!
This is our third online poll in our series to celebrate the International Year of Astronomy 2009. Choose your favourite question from the list on the right, and we'll put the one that proves most popular to world-leading astronomers and cosmologists, including Astronomer Royal Martin Rees and author and cosmologist John D. Barrow. The poll will
remain open for a month and the answer will be published in a Plus article and podcast soon after. If your most burning question is not on this list, then leave a comment on this blog and we'll endeavour to include it in a future poll — there will be four more polls dotted throughout the year.
Dark matter is possibly "easy" to determine: neutrinos have mass. That simple (but hugely ignored) fact could provide both sufficient mass and energy to explain the otherwise unobserved masses and energies that puzzle us.
But how Gravity works - well, that's something I would really like to know.
Next time you're off to the bookies to place your footie bets, you might be better off consulting a statistician than a football expert. On his Understanding Uncertainty website self-confessed football un-enthusiast David Spiegelhalter used a simple statistical model to predict the results of the last ten Premier League matches, which were played on the 24th of May 2009. In terms of predicting whether a game ended in a win, draw, or defeat for the home team, Spiegelhalter's model was right nine out of ten times, compared to the seven out of ten score achieved by the official BBC football expert Marc Lawrenson, and the model predicted two scores exactly.
Spiegelhalter and his co-authors Mike Pearson and Ian Short quantified the individual teams' attack strength and defense weakness based on their past performance, and then, with a little help from probability theory, used these ratings to work out the most likely outcome of a particular match. (You can see the details of this model on his website.) "These types of models have been refined over the years and are now used by bookies and sports betting companies, who employ experienced statisticians and make use of the latest computational methods," says Spiegelhalter. But he concedes that his very basic model might have been a bit lucky this time: "One thing you can bet on is that
simple models like this one will be very unlikely to out-perform the odds being offered by bookies, so don't use them to spot good bets!"
Spiegelhalter announced his prediction on the BBC Radio 4 programme More or Less, which was aired before the final match day, so you can be sure that no hindsight fraud was involved.
David Spiegelhalter is Winton Professor for the Public Understanding of Risk at the University of Cambridge and regularly writes for Plus (see for example his article on the 2006-2007 Premier League season). His Understanding Uncertainty website is designed to inform the
public about everything to do with risk and uncertainty, from health scares to predicting election results.
davids approach seems quite nice to me, so i think it takes into account all the strength and weakensses of both the teams, now leaving the thrill factor (which is still very much alive,as it is a guide only) i think if one is thinking of investing in sports picks ,the theory appears nice in principle,
At the very heart of sport is a fierce battle in which the combatants strive to outwit and outplay each other. Each thrust is matched by a parry and in the end, there can only be one winner. The rules of each sport dictate how that winner is determined, and whether it is football, tennis, golf or chess, it is those who perform best on the day who take home the glory. This latest installment of
the Plus sports page looks at two ranking systems that couldn't be any different from each other — those of sumo and chess.
Are you disappointed because ITV's "most stressful game show on TV", The colour of money, seems to have been pulled? Do you think that you had just the right strategy to win? Then check out if you were right with John Haigh's analysis of best play.
Looking for something to think about next time you gaze at your reflection when brushing your teeth? Then Sara Santos has some mathematical inspiration for your next daydream in her MMP public lecture, Through the looking glass... again and again!. If Alice took a magic trip inside a conic arrangement of mirrors, what would she find in this
mathematical wonderland? You can take a look through a 3D kaleidoscope to see what happens to Alice's cubes and icosahedrons!
Sara Santos is Clothworkers' Fellow in mathematics at The Royal Institution of Great Britain (Ri) and is responsible for coordinating the UK-wide network of secondary Ri mathematics masterclasses. Sara will be speaking at 11am on Thursday 11 June 2009, at the Centre for Mathematical Sciences, Cambridge, just down the hall from Plus! Admission to the
lecture is free but by ticket only — for tickets please contact Kerstin Enright, Millennium Mathematics Project, Centre for Mathematical Sciences, Wilberforce Road, Cambridge CB3 0WA (01223 766839) or email: firstname.lastname@example.org. You can also sign up for notifications of future MMP events at the MMP site.
And don't forget you can also see the London Mathematical Society's popular lectures on Monday 22 June in London and Tuesday 15 September in Birmingham. Come and see how physicists helped answer a hundred year old question about prime numbers and how random matrices and Riemann zeroes feature in a major Hollywood movie with Nina Smith. And Mark Miodownik will
explain how fleas can jump over 100 times their own height, flies can walk on water and a hamster can survive falling from aircraft without a parachute.
Admission is free, but by ticket only. For more information and tickets, contact Lee-Anne Parker, London Mathematical Society, De Morgan House, 57-58 Russell Square, London,WC1B 4HS (email: email@example.com), or visit the LMS website.