Mathematician

Irénée-Jules Bienaymé

Modern

Irénée-Jules Bienaymé, who always used the name Jules, was a French statistician, born in Paris on 28 August 1796. He built on the legacy of Laplace by generalising his least squares method, and contributed to probability and statistics and to their application to finance, demography and the social sciences. He formulated the Bienaymé-Chebyshev inequality concerning the law of large numbers and the Bienaymé formula for the variance of a sum of uncorrelated random variables. After he left the civil service he lectured on probability at the Faculty of Sciences, and from 1852 he sat in the Paris Academy of Sciences, serving for 23 years as referee for its statistics prize. He died in Paris in 1878.

Facts
Biography
Gender
Male 1
Birth Year
1796 2
Connections

In Branch

Source MacTutor History of Mathematics, University of St Andrews: Irénée-Jules Bienaymé (biography)

Principal Result

Source Irénée-Jules Bienaymé (Wikipedia)
In the Other Atlases

Nationality

Also in Geography Atlas: the nationality of this subject.

Source Irénée-Jules Bienaymé (Wikipedia)Lead, nationality
Quote, Lead, nationality
was a French statistician.
Sources
1. MacTutor History of Mathematics, University of St Andrews: Irénée-Jules Bienaymé (biography)
MacTutor History of Mathematics, University of St Andrews
  • Biography, pronoun
    However, he did not use the name, always using the name Jules.
  • In Branch: Probability and Statistics, Biography, lectures on probability
    Shortly after he left the Civil Service he was asked to give a lecture course on probability at the Faculty of Sciences.
View the Source
2. Irénée-Jules Bienaymé (Wikipedia)
  • Lead, birth and death dates
    (French: [iʁene ʒyl bjɛ̃nɛme]; 28 August 1796-19 October 1878)
  • Lead, nationality
    was a French statistician.
  • Principal Result: Chebyshev's Inequality, Lead, inequality
    he formulated the Bienaymé-Chebyshev inequality concerning the law of large numbers and the Bienaymé formula for the variance of a sum of uncorrelated random variables
View the Source

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