Probability theory, Applied Statistics

Origin and Development of probability Theory:

The credit for origin and development of probability goes to the European gamblers of 17th century. They  used to gamble  on games  of  chance  such as throwing  a dice, tossing  up a coin , horse  race, drawing  cards from a pack of cards etc.  For getting success in above games of chances. They started getting the help of mathematicians. By the deep study and calculations of these mathematicians the theory of probability originated. 

All Italian Mathematician Jerome cardoon(1501-1576)   was the first person to write a book on probability, Games  of chances which was published after his  death in 1663. In  this  book he mentioned all risks involved  and rules how to lessen  those risks  Galileo (1564-1642)  an Italian Mathematician, attempted  quantitative   measures  of probability for solving  the problems related  to the theory of dice in gambling. In  mid 17th century two French mathematicians  Blaise  Pascal (1623-1662)    mce_markernbsp; pierre   de fermat  gave  the systematic and scientific foundation of mathematical  theory  of probability. Swisss mathematician  James Bernoulli (1654-1705)  was another  brave and  strong man who made extensive study of the subject  for 2 decades  and introduced Bernoulli theorem and its theory in his book air conjectandi published in 1713  after his death in major contribution to the modern theory    of probability. In 1718 Abrahm de Moivre  (1667-1754)  published his book The  Doctrine of chances and contributed a lot to this subject.   

In 18th &19th century many mathematicians tried to develop scientific method for the development of different theorems of probability. Thomas Bayes (1702-1761) introduced the concept of inverse probability which is also known as bayes . Theorem Pierre Simon   de Laplace (1749-1827) after an extensive research published his book. Theory of Analytical  probability which constitutes the classical theory  of probability; Ronald fisher and von mises introduced empirical approach probability through an idea of sample  space, In 1926   mathematician frank Ramsey published his work the foundation of mathematics and other logical essays  in  which he introduced the theory  of subjective approach to probability. Which was developed  by Richard good Bernard, Coopman  and Lleonard  sweage. This concept is especially used in statistical decision theory.

The modern theory  of probability  was developed by a number of Russian   mathematicians like  Chebychev (1821-1894)  A  markov (1856-1922)  and A .N Kolmogarov. Kolmogarov axionised   the  theory  of probability  and  he published his work foundations of probability  in 1933  in which he introduced  probability as set function and regarded as a classic. 

Posted Date: 9/27/2012 6:54:16 AM | Location : United States







Related Discussions:- Probability theory, Assignment Help, Ask Question on Probability theory, Get Answer, Expert's Help, Probability theory Discussions

Write discussion on Probability theory
Your posts are moderated
Related Questions

First we look at these charts assuming that we know both the mean and the standard deviation of the process, that is  μ and  σ . These values represent the acceptable values (bench

Statistics Can Lead to Errors The use of statistics can often lead to wrong conclusions or wrong estimates. For example, we may want to find out the average savings by i

Collect data about the chosen business problem or opportunity at the company. Explain how you obtained a suitable sample of either qualitative or quantitative data. Review data f

Systematic Sampling In Systematic Sampling each element has an equal chance of being selected, but each sample does not have the same chance of being selected. Here,

How can we analyse data with four bilateral response variables measured with errors and three covariated measured without errors?

If the economy does well, the investor's wealth is 2 and if the economy does poorly the investor's wealth is 1. Both outcomes are equally likely. The investor is offered to invest

Median Median is a position average. It is the value of middle item of a variable when the items are arranged according to their values either in ascending or descending order.

Consider a Cournot duopoly with two firms (fi rm 1 and fi rm 2) operating in a market with linear inverse Demand P(Q) = x Q where Q is the sum of the quantities produced by both

In a three-cornered paint ball duel, A, B, and C successively take shots at each other until only one of them remains paint free. Once hit, a player is out of the game and gets no