Probability theory, Applied Statistics

Assignment Help:

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. 


Related Discussions:- Probability theory

Find probability of remaining paint free - ball duel, In a three-cornered p...

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

Chi-square analysis, Chi-square analysis can be used with both Goodness-of-...

Chi-square analysis can be used with both Goodness-of-Fit Tests and with Tests for Independence. There are specific instances when each test should be used based on the information

Statistical definition of probability, Statistical Definition of probabilit...

Statistical Definition of probability: Ques: (a) (i)  Distinguish Statistical Definition of probability from the Classical Definition.                  (ii) State the A

Correlation, prove that coefficient of correlation lies between -1 and+1

prove that coefficient of correlation lies between -1 and+1

Regression lines, Regression Lines It has already been discussed that t...

Regression Lines It has already been discussed that there are two regression lines and they show mutual relationship between two variable . The regression line Yon X gives   th

Root mean square deviation, Root Mean Square Deviation The standard d...

Root Mean Square Deviation The standard deviation is also called the ROOT MEAN SQUARE DEVIATION. This is because it is the ROOT (Step 4) of the MEAN (Step 3) o

Heteroskedastic-consistent standard errors, The following table shows the r...

The following table shows the results of fitting a linear regression model of starting annual salaries on a constant, GPA (4 point scale), and a variable (Metrics =1) indicating wh

Practice-Based Evidence, how to analyzePractice-Based Evidence Back to the ...

how to analyzePractice-Based Evidence Back to the Future

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd