What Is Probability?
The study of probability arose from interest in games and
gambling which have been around since ancient civilization.
Around 5000 years ago, Egyptians were using the astragalus, a
bone found in the heel of mammals, as a random
device just as
we use dice now. When thrown, the astragalus lands on one of its four
sides, but not with equal frequency.
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Mesopotamians played a game of strategy and chance as long as 4500 years ago. Gambling was a common pastime in the Roman Empire but was only permitted on certain holidays. Some of the most famous Roman gamblers were the emperors Augustus (63 BCE-AD 14) and Vitellius (AD 15-69). Games and gambling stayed popular across many years and cultures. In the time of Gerolamo Cardano (1501-1576), many types of games included a wager. Gerolamo noticed patterns in the games of chance and bet according to those patterns. His observations made him a successful gambler and he soon earned enough to support himself as a medical student.
Cardano has been called the Father of Probability
because
of his observations about random processes. His published
definition of probability provided a basis for further study of
probability (Mlodinow, 2009). Before his time, the study of
probability was limited due to a general discomfort with the idea
of randomness,
explained by the time's religious ideology.
Randomness is the occurrence of events with short-term
unpredictability. Since it was commonly believed that God or the
gods controlled everything, admitting the idea of
randomness
was heresy.
From the time of Cardano until the 19th century, the concept of uncertainty in games of chance combined with religious ideas to contribute to the deterministic view of the universe. A deterministic philosophy was characterized by the belief that if a person knew enough initial conditions, they could determine any outcome. In the early 19th century, mathematicians, such as Pierre Simon de Laplace (1749-1827), explained any deviations from predictions by attributing them to imprecise measurement tools. However, with more sophisticated tools, the variability increased. This led to the development of the concept of random chance—that some level of unpredictability always exists despite knowledge of initial conditions, which informs the theories underlying modern probability theory and statistical methods (Salsburg, 2001).
The theory of probability deals with the long-term outcomes of chance processes. It helps anticipate the action that is most likely to result in a favorable outcome. It recognizes that randomness causes unpredictability for one particular result but high predictability for results from a frequently repeated random process.
Pierre Simon de Laplace said:
The most important questions of life are, for the most part, really only problems of probability… [I]n the small number of things which we are able to know with certainty, even in the mathematical sciences themselves, induction and analogy, the principal means for discovering truth, are based on probabilities, so that the entire system of human knowledge is connected with this theory… It is remarkable that probability, which began with the consideration of games of chance, should have become the most important object of human knowledge (Lightner, 1991, p. 628).