Today, at lunch, Matthieu told us a nice story (or call it a paradox if you like) about the probability to find you seat empty when you get in a place. a plane full of nuns Assume that you are in the line to get in the airplane, you are the ...

Simple root finding and one dimensional integrals algorithms were implemented in previous posts. These algorithms can be used to estimate the cumulative probabilities and quantiles. Here, take normal distribution as an example. Read More: 281 Words Totally

SOME EMPIRICAL BASES FOR CHOOSING CERTAIN RISK REPRESENTATIONS OVER OTHERS This week DSN posts some thoughts (largely inspired by the work of former colleagues Stephanie Kurzenhäuser, Ralph Hertwig, Ulrich Hoffrage, and Gerd Gigerenzer) about communicating risks to the general public, providing references and delicious downloads where possible. Representations to use less often Single-event probabilities as

Toss one hundred different balls into your basket. Shuffle them up and select one with equal probability amongst the balls. That ball you just selected, it’s special. Before you put it back, increase its weight by 1/100th. Then put it back, mix up the balls and pick again. If you do this enough, at some

Imagine a unit square. Every side has length 1, perfectly square. Now imagine this square was really a fence, and you picked two spots at random along the fence, with uniform probability over the length of the fence. At each of these two locations, set down a special kind of cannon. Just like the light

In math and economics, there is a long, proud history of placing imaginary prisoners into nasty, complicated scenarios. We have, of course, the classic Prisoner’s Dilemma, as well as 100 prisoners and a light bulb. Add to that list the focus of this post, 100 prisoners and 100 boxes. In this game, the warden places

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