![]() Student), a means of testing the statistical significance of the difference between two sample means. Gosset (1876-1937) used labeled cards to help develop and test the t-test (under the penname A. Darwin's nephew) described a general simulation method using modified dice to generate a normal distribution and W. Darwin (1845-1912 Charles Darwin's son) used a spinner in an algorithm to smooth curves F. De Forest (1834-1888), used a specially labeled card deck to develop and test a method of smoothing mortality tables G. ![]() In the nineteenth and early twentieth centuries, simulation was increasingly used as an experimental means of confirming theory, analyzing data, or supplementing intuition in mathematical statistics. (There are websites that will perform this experiment for you, e.g.) Some consider LeClerc's experiment the first instance of Monte Carlo simulation.īuffon's Needle: after N tosses, the estimate for pi is (2N/X), where X is the number of times the needle intersects a line. He tested this by tossing baguettes over his shoulder onto a tile floor. LeClerc proved that for a needle the same length as the distance between the lines, the probability of the needle intersecting a line was 2/π. He used random methods in a number of studies, most famously “Buffon's needle,” a method using repeated needle tosses onto a lined background to estimate π ( Fig. It can be traced back at least to the eighteenth century, to Georges Louis LeClerc, Comte de Buffon (1707-1788), an influential French scientist. The idea of using randomness in a determinative manner was revolutionary. ![]() And yet Monte Carlo simulation, which is, essentially, a series of coin flips, is used to explore these areas and many, many more. However, it is somewhat counterintuitive to think that flipping the coin millions, billions or trillions of times could give us insight into what is happening in a nuclear reactor, into tomorrow's weather, or into our current recession. “Do random events ever lead to concrete results? Seems unlikely – after all, they're random.” Clearly, if we want to know how likely heads and tails are for a particular coin, flipping the coin thousands of times would give us an estimate.
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