Overview: Timeline and Context

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Presentation transcript:

Overview: Timeline and Context November 6, 2010 Santa Fe Alliance for Science Professional Enrichment Activity

Games of Chance in History and Literature Humans have played games of chance for thousands of years. Forms of dice have been found, dating back as far as 3000 BCE. Gambling (specifically, gambling and losing) is mentioned in one of the oldest religious texts in the world, the Rigveda, composed ~1500 BCE. Several songs in the Carmina Burana manuscript (11th– 13th century CE) use games of chance (and again, losing at games of chance) as their subjects. Theoretical foundations = what we know from the research literature on girls participation in STEM/ICT programs Best practices = what we have found to work in our own programs

Much Later, Analysis De Vetula, a 13th-century Latin long poem, includes (in its accompanying non-poetic content) what is believed to be the earliest known analysis of a game of chance. The text enumerates the combinations possible in a throw of three dice, and attempts to explain the relationship between number of combinations producing a given total and the anticipated frequency of that total. Though many scientists and mathematicians (including Cardano, Tartaglia, and Galileo) devoted at least some study to games of chance (usually at the request of gambling patrons), the first known rigorous mathematical analysis of a game of chance was in 1654, in a series of letters between Blaise Pascal and Pierre de Fermat. Theoretical foundations = what we know from the research literature on girls participation in STEM/ICT programs Best practices = what we have found to work in our own programs

Early Applications in Demographics In 1663, John Graunt published the demographic work, Natural and Political Observations upon the Bills of Mortality, viewed by some as marking the origin of statistics as a field of study. In 1693, Edmond Halley gave the first demonstration of the field now known as actuarial science, by showing how probability theory and demographic data could be used to compute life insurance premiums.

Generalization of the Use of Statistics In the late 18th and early 19th centuries, the field of statistics began to expand beyond demographics to encompass general data analysis. In a key milestone, Carl Friedrich Gauss combined calculus, probability theory, and descriptive statistics to invent (~1795) the method of least squares for linear regression – still an essential tool for data analysis today.

Modern Computation and Applications Today, the wide availability of advanced computational resources makes possible statistical analyses that could not be performed in the past – not just increasing the amount of data that can be handled, but supporting the invention and use of methods that were previously inconceivable (or at best, wildly impractical).