"A gambler's dispute in 1654 led to the creation of a mathematical theory of probability by two famous French mathematicians, Blaise Pascal and Pierre de Fermat. Antoine Gombaud, Chevalier de Méré, a French nobleman with an interest in gaming and gambling questions, called Pascal's attention to an apparent contradiction concerning a popular dice game. The game consisted in throwing a pair of dice 24 times; the problem was to decide whether or not to bet even money on the occurrence of at least one "double six" during the 24 throws. A seemingly well-established gambling rule led de Méré to believe that betting on a double six in 24 throws would be profitable, but his own calculations indicated just the opposite.

This problem and others posed by de Méré led to an exchange of letters between Pascal and Fermat in which the fundamental principles of probability theory were formulated for the first time. Although a few special problems on games of chance had been solved by some Italian mathematicians in the 15th and 16th centuries, no general theory was developed before this famous correspondence.

The Dutch scientist Christian Huygens, a teacher of Leibniz,
learned of this correspondence and shortly thereafter (in 1657)
published the first book on probability; entitled
*De Ratiociniis in Ludo Aleae*, it was a treatise on problems
associated with gambling.
Because of the inherent appeal of games of chance,
probability theory soon became popular,
and the subject developed rapidly during the 18th century.
The major contributors during
this period were Jakob Bernoulli (1654-1705) and Abraham de
Moivre (1667-1754).

In 1812 Pierre de Laplace (1749-1827) introduced a host of
new ideas and mathematical
techniques in his book, *Théorie Analytique des Probabilités*.
Before Laplace, probability
theory was solely concerned with developing a mathematical
analysis of games of chance.
Laplace applied probabilistic ideas to many scientific and
practical problems. The theory
of errors, actuarial mathematics, and statistical mechanics are
examples of some of the important applications of probability
theory developed in the l9th century.

Like so many other branches of mathematics, the development of probability theory has been stimulated by the variety of its applications. Conversely, each advance in the theory has enlarged the scope of its influence. Mathematical statistics is one important branch of applied probability; other applications occur in such widely different fields as genetics, psychology, economics, and engineering. Many workers have contributed to the theory since Laplace's time; among the most important are Chebyshev, Markov, von Mises, and Kolmogorov.

One of the difficulties in developing a
mathematical theory of probability has been to arrive at a
definition of probability
that is precise enough for use in mathematics, yet
comprehensive enough to be
applicable to a wide range of phenomena. The search for a widely
acceptable definition
took nearly three centuries and was marked by much
controversy. The matter was
finally resolved in the 20th century by treating probability
theory on an axiomatic basis.
In 1933 a monograph by a Russian mathematician A. Kolmogorov outlined an
axiomatic approach that forms the basis for the modern theory.
(Kolmogorov's monograph is available in
English translation as *Foundations of Probability Theory*,
Chelsea, New York, 1950.)
Since then the ideas have been refined somewhat and probability
theory is now part
of a more general discipline known as measure theory."