Charles writes, "It's hard to imagine how we would have gotten all of the whiz-bang technology we enjoy today without the discovery of probability and statistics. From vaccines to the Internet, we owe a lot to the probabilistic revolution, and every great revolution deserves a great story!

"The Fields Institute for Research in Mathematical Sciences has partnered up with the American Statistical Association in launching a speculative fiction competition that calls on writers to imagine a world where the Normal Curve had never been discovered. Stories will be following in the tradition of Gibson and Sterling's steampunk classic, The Difference Engine, in creating an imaginative alternate history that sparks the imagination. The winning story will receive a $2000 grand prize, with an additional $1500 in cash available for youth submissions."

What would the world be like if the Normal Curve had never been discovered? (*Thanks, Charles!*)
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Charles writes, "It's hard to imagine how we would have gotten all of the whiz-bang technology we enjoy today without the discovery of probability and statistics. From vaccines to the Internet, we owe a lot to the probabilistic revolution, and every great revolution deserves a great story!

"The Fields Institute for Research in Mathematical Sciences has partnered up with the American Statistical Association in launching a speculative fiction competition that calls on writers to imagine a world where the Normal Curve had never been discovered. Stories will be following in the tradition of Gibson and Sterling's steampunk classic, The Difference Engine, in creating an imaginative alternate history that sparks the imagination. The winning story will receive a $2000 grand prize, with an additional $1500 in cash available for youth submissions."

What would the world be like if the Normal Curve had never been discovered? (*Thanks, Charles!*)
]]>

Some German researchers are trying to make that process a little easier, using a computer model and a whole lot of probability power. They published a paper about this method recently, using their system to estimate an 80% likelihood that the 2010 Russian heatwave was the result of climate change. Wired's Brandon Keim explains how the system works:

]]>The new method, described by Rahmstorf and Potsdam geophysicist Dim Coumou in an Oct. 25 Proceedings of the National Academy of Sciences study, relies on a computational approach called Monte Carlo modeling. Named for that city’s famous casinos, it’s a tool for investigating tricky, probabilistic processes involving both defined and random influences: Make a model, run it enough times, and trends emerge.

“If you roll dice only once, it doesn’t tell you anything about probabilities,” said Rahmstorf. “Roll them 100,000 times, and afterwards I can say, on average, how many times I’ll roll a six.”

Rahmstorf and Comou’s “dice” were a simulation made from a century of average July temperatures in Moscow. These provided a baseline temperature trend. Parameters for random variability came from the extent to which each individual July was warmer or cooler than usual.

After running the simulation 100,000 times, “we could see how many times we got an extreme temperature like the one in 2010,” said Rahmstorf. After that, the researchers ran a simulation that didn’t include the warming trend, then compared the results.

“For every five new records observed in the last few years, one would happen without climate change. An additional four happen with climate change,” said Rahmstorf. “There’s an 80 percent probability” that climate change produced the Russian heat wave.

Some German researchers are trying to make that process a little easier, using a computer model and a whole lot of probability power. They published a paper about this method recently, using their system to estimate an 80% likelihood that the 2010 Russian heatwave was the result of climate change. Wired's Brandon Keim explains how the system works:

]]>The new method, described by Rahmstorf and Potsdam geophysicist Dim Coumou in an Oct. 25 Proceedings of the National Academy of Sciences study, relies on a computational approach called Monte Carlo modeling. Named for that city’s famous casinos, it’s a tool for investigating tricky, probabilistic processes involving both defined and random influences: Make a model, run it enough times, and trends emerge.

“If you roll dice only once, it doesn’t tell you anything about probabilities,” said Rahmstorf. “Roll them 100,000 times, and afterwards I can say, on average, how many times I’ll roll a six.”

Rahmstorf and Comou’s “dice” were a simulation made from a century of average July temperatures in Moscow. These provided a baseline temperature trend. Parameters for random variability came from the extent to which each individual July was warmer or cooler than usual.

After running the simulation 100,000 times, “we could see how many times we got an extreme temperature like the one in 2010,” said Rahmstorf. After that, the researchers ran a simulation that didn’t include the warming trend, then compared the results.

“For every five new records observed in the last few years, one would happen without climate change. An additional four happen with climate change,” said Rahmstorf. “There’s an 80 percent probability” that climate change produced the Russian heat wave.