The Art of Statistics: Learning From Data
by
David Spiegelhalter
Published 14 Oct 2019
Following good 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 his time collecting data on his successes – he would simply have simulated thousands of games. Figure 8.1 displays the results of such a simulation, showing how the overall proportion of times that he wins each game changes as he ‘plays’ more and more. Although Game 2 looks the better bet for a while, after around 400 games of each it becomes clear that Game 1 is better, and in the (very) long run he can expect to win around 52% of Game 1, and only 49% of Game 2.
The Art of Statistics: How to Learn From Data
by
David Spiegelhalter
Published 2 Sep 2019
Following good 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 his time collecting data on his successes—he would simply have simulated thousands of games. Figure 8.1 displays the results of such a simulation, showing how the overall proportion of times that he wins each game changes as he ‘plays’ more and more. Although Game 2 looks the better bet for a while, after around 400 games of each it becomes clear that Game 1 is better, and in the (very) long run he can expect to win around 52% of Game 1, and only 49% of Game 2.
Fermat’s Last Theorem
by
Simon Singh
Published 1 Jan 1997
The mathematical hermit was introduced to the subject by Pascal, and so, despite his desire for isolation, he felt obliged to maintain a dialogue. Together Fermat and Pascal would discover the first proofs and cast-iron 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 whichever player is the first to earn a certain number of points is the winner and takes the prize money. Gombaud had been involved in a game of points with a fellow-gambler when they were forced to abandon the game half-way through, owing to a pressing engagement.
The Drunkard's Walk: How Randomness Rules Our Lives
by
Leonard Mlodinow
Published 12 May 2008
Often in history the study of the random has been aided by an event that was itself random. Pascal’s work represents such an occasion, for it was his abandonment of study that led him to the 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 an expert gambler who liked the stakes high and won often enough that some suspected him of cheating. And when he stumbled on a little gambling quandary, he turned to Pascal for help.
Against the Gods: The Remarkable Story of Risk
by
Peter L. Bernstein
Published 23 Aug 1996
Radical Uncertainty: Decision-Making for an Unknowable Future
by
Mervyn King
and
John Kay
Published 5 Mar 2020
Alex's Adventures in Numberland
by
Alex Bellos
Published 3 Apr 2011
What We Cannot Know: Explorations at the Edge of Knowledge
by
Marcus Du Sautoy
Published 18 May 2016
Money: The True Story of a Made-Up Thing
by
Jacob Goldstein
Published 14 Aug 2020
Safe Haven: Investing for Financial Storms
by
Mark Spitznagel
Published 9 Aug 2021
Is God a Mathematician?
by
Mario Livio
Published 6 Jan 2009
Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets
by
Nassim Nicholas Taleb
Published 1 Jan 2001
The Perfect Bet: How Science and Math Are Taking the Luck Out of Gambling
by
Adam Kucharski
Published 23 Feb 2016
At the request of a group of Italian nobles, Galileo investigated why some combinations of dice faces appeared more often than others. Astronomer Johannes Kepler also took time off from studying planetary motion to write a short piece on the theory of dice and gambling. The science of chance blossomed in 1654 as the result of a gambling question posed by a French writer named Antoine Gombaud. He had been puzzled by the following dice problem. Which is more likely: throwing a single six in four rolls of a single die, or throwing double sixes in twenty-four rolls of two dice? Gombaud believed the two events would occur equally often but could not prove it. He wrote to his mathematician friend Blaise Pascal, asking if this was indeed the case.
The Physics of Wall Street: A Brief History of Predicting the Unpredictable
by
James Owen Weatherall
Published 2 Jan 2013
Wonderland: How Play Made the Modern World
by
Steven Johnson
Published 15 Nov 2016
Written in 1564, Cardano’s book wasn’t published for another century. By the time his ideas got into wider circulation, an even more important breakthrough had emerged out of a famous correspondence between Blaise Pascal and Pierre de Fermat in 1654. This, too, was prompted by a compulsive gambler, the French aristocrat Antoine Gombaud, who had written Pascal for advice about the most equitable way to predict the outcome of a dice game that had been interrupted. Their exchange put probability theory on a solid footing and created the platform for the modern science of statistics. Within a few years, Edward Halley (of comet legend) was using these new tools to calculate mortality rates for the average Englishman, and the Dutch scientist Christiaan Huygens and his brother Lodewijk had set about to answer “the question . . . to what age a newly conceived child will naturally live.”
How I Became a Quant: Insights From 25 of Wall Street's Elite
by
Richard R. Lindsey
and
Barry Schachter
Published 30 Jun 2007
Statistics in a Nutshell
by
Sarah Boslaugh
Published 10 Nov 2012
God Created the Integers: The Mathematical Breakthroughs That Changed History
by
Stephen Hawking
Published 28 Mar 2007