Antoine Gombaud: Chevalier de Méré Concepts

Fermat’s Last Theorem

by Simon Singh · 1 Jan 1997 · 289pp · 85,315 words

certainties in probability theory, a subject which is inherently uncertain. Pascal’s interest in the subject had been sparked by a professional Parisian gambler, Antoine Gombaud, the Chevalier de Méré, who had posed a problem which concerned a game of chance called points. The game involves winning points on the roll of a dice, and

Everything Is Predictable: How Bayesian Statistics Explain Our World

by Tom Chivers · 6 May 2024 · 283pp · 102,484 words

than half. You’d lose money betting on it. What’s gone wrong? A century or so later, in 1654, Antoine Gombaud, a gambler and amateur philosopher who called himself the Chevalier de Méré, was interested in the same questions, for obvious professional reasons. He had noticed exactly what we’ve just said: that betting

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.-A, Serret 3 (1869): 441–76; Serret 5 (1870): 663–84 (Paris: Gauthier-Villars), cited in Bellhouse, “The Reverend Thomas Bayes.” 23. P. Gorroochurn, “The Chevalier de Méré Problem I: The Problem of Dice (1654),” in Classic Problems of Probability, ed., P. Gorroochurn (Hoboken, NJ: John Wiley & Sons, 2012), 14, https://doi.org

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, Andrew, 18–19 DeepMind, 221 de Finetti, Bruno, 106, 110, 197 Defoe, Daniel, 23 degree of certainty, 49–52 DeGroot, Morris, 110 de Méré, Chevalier (Antoine Gombaud), 37–38 Democritus, 271 de Moivre, Abraham, 27, 53–61, 73, 77 depression, 308–313 derivatives, 34–35 dice gambling, 35–38 Diogenes, 266 Dissenters

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–203 Gardner, Martin, 247 “Gaudeamus Igitur,” 112 gaze heuristic, 238–239 genomes, 323–324 Gigerenzer, Gerd, 19, 238 glasnost, 251 Goldacre, Ben, 11 Gombaud, Antoine (Chevalier de Méré), 37–38 Good, I. J. “Jack,” 110 Google, 159, 168, 209, 322 Google Scholar, 172 Gorbachev, Mikhail, 251 Gorroochurn, Prakash, 39–40 “Grad Student Who

The Art of Statistics: Learning From Data

by David Spiegelhalter · 14 Oct 2019 · 442pp · 94,734 words

.3 Bootstrap Distribution of Means at Varying Sample Sizes 7.4 Bootstrap Regressions on Galton’s Mother–Daughter Data 8.1 A Simulation of the Chevalier de Méré’s Games 8.2 Expected Frequency Tree for Two Coin Flips 8.3 Probability Tree for Flipping Two Coins 8.4 Expected Frequency Tree for

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of the population and do not require complex probability theory. CHAPTER 8 Probability – the Language of Uncertainty and Variability In 1650s France, the self-styled Chevalier de Méré had a gambling problem. It was not that he gambled too much (although he did), but he wanted to know which of two games he

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empirical statistical principles, the Chevalier de Méré decided to play both games numerous times and see how often he won. This took a great deal of time and effort, but in a bizarre parallel universe in which there were computers but no probability theory, the good Chevalier (real name Antoine Gombaud) would not have wasted

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does not affect the other) occurring. For example, the probability of a head AND a head is ½ × ½ = ¼. These basic rules allow us to solve the Chevalier de Méré’s gambling problem, revealing that he does indeed have a 52% chance of winning Game 1, and a 49% chance of winning Game 2.1

The Art of Statistics: How to Learn From Data

by David Spiegelhalter · 2 Sep 2019 · 404pp · 92,713 words

.3 Bootstrap Distribution of Means at Varying Sample Sizes 7.4 Bootstrap Regressions on Galton’s Mother—Daughter Data 8.1 A Simulation of the Chevalier de Méré’s Games 8.2 Expected Frequency Tree for Two Coin Flips 8.3 Probability Tree for Flipping Two Coins 8.4 Expected Frequency Tree for

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of the population and do not require complex probability theory. CHAPTER 8 Probability—the Language of Uncertainty and Variability In 1650s France, the self-styled Chevalier de Méré had a gambling problem. It was not that he gambled too much (although he did), but he wanted to know which of two games he

…

empirical statistical principles, the Chevalier de Méré decided to play both games numerous times and see how often he won. This took a great deal of time and effort, but in a bizarre parallel universe in which there were computers but no probability theory, the good Chevalier (real name Antoine Gombaud) would not have wasted

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entire ‘branch’ of the tree is obtained by multiplying the fractions on the splits along the branch. These basic rules allow us to solve the Chevalier de Méré’s gambling problem, revealing that he does indeed have a 52% chance of winning Game 1, and a 49% chance of winning Game 2.1

The Drunkard's Walk: How Randomness Rules Our Lives

by Leonard Mlodinow · 12 May 2008 · 266pp · 86,324 words

study of chance. It all began when one of his partying pals introduced him to a forty-five-year-old snob named Antoine Gombaud. Gombaud, a nobleman whose title was chevalier de Méré, regarded himself as a master of flirtation, and judging by his catalog of romantic entanglements, he was. But de Méré was also

Radical Uncertainty: Decision-Making for an Unknowable Future

by Mervyn King and John Kay · 5 Mar 2020 · 807pp · 154,435 words

to be that which the many think?’ PHAEDRUS: ‘Certainly, he does.’ —PLATO , Phaedrus 1 T he ‘probabilistic turn’ in human reasoning reportedly began when the Chevalier de Méré, an inveterate gambler, sought the advice of the mathematician and philosopher Blaise Pascal. Pascal in turn consulted an even more distinguished French polymath, Pierre de

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community. The probabilistic turn led modern economists and other social scientists to proceed firmly down the probabilistic road. The problem of points The question the Chevalier de Méré had put to Pascal, which led to the modern theory of probability, was ‘the problem of points’. Suppose a game of chance in the Chevalier

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hard to imagine an environment and company less congenial to the Reverend Bayes than that which he would have encountered in the salon of the Chevalier de Méré. But let us take a flight of imagination and place him there, keeping score on a ‘Bayesian dial’ above the elegant mantelpiece. On the clock

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to breast cancer are more likely to seek mammograms than women who are not. In games of chance, such as the wagers that prompted the Chevalier de Méré to contemplate the problem of points or the Monty Hall problem, everything is either known or unknown, deterministic or random. But that dichotomy does not

Statistics in a Nutshell

by Sarah Boslaugh · 10 Nov 2012

large part on her understanding the probability of different events within the chosen game. Many historians trace the beginning of modern probability theory to the Chevalier de Mere, a gentleman gambler in seventeenth-century France. He was fond of betting that he would roll at least one six in four rolls of a

God Created the Integers: The Mathematical Breakthroughs That Changed History

by Stephen Hawking · 28 Mar 2007

ball; this bet is even advantageous in four drawings; it returns then to that of throwing six in four throws with a single die. The Chevalier de Meré, who caused the invention of the calculus of probabilities by encouraging his friend Pascal, the great geometrician, to occupy himself with it, said to him

Against the Gods: The Remarkable Story of Risk

by Peter L. Bernstein · 23 Aug 1996 · 415pp · 125,089 words

religious turmoil, nascent capitalism, and a vigorous approach to science and the future. In 1654, a time when the Renaissance was in full flower, the Chevalier de Mere, a French nobleman with a taste for both gambling and mathematics, challenged the famed French mathematician Blaise Pascal to solve a puzzle. The question was

The Norm Chronicles

by Michael Blastland · 14 Oct 2013

lost him a lot of money. You can try this as well. (The odds would be 50:50 only if there were no repeats.) The Chevalier de Méré, a more perceptive gambler, in Paris in the 1650s, reckoned from his gaming that if he bet that he could throw a 6 in four