Laplace, Pierre Simon de (1749-1827) - PowerPoint PPT Presentation

About This Presentation
Title:

Laplace, Pierre Simon de (1749-1827)

Description:

He then introduced the Characteristic function: If is a sample of i.i.d. obs. ... that led to the modern characteristic function approach to the Central Limit ... – PowerPoint PPT presentation

Number of Views:1669
Avg rating:3.0/5.0
Slides: 17
Provided by: Eare1
Category:

less

Transcript and Presenter's Notes

Title: Laplace, Pierre Simon de (1749-1827)


1
Laplace, Pierre Simon de (1749-1827)

2
Agenda
  • Biography
  • History of The Central limit Theorem (CLT)
  • Derivation of the CLT
  • First Version of the CLT
  • CLT for the Binomial Distribution
  • Laplace and Bayesian ideas
  • 4th and 5th Principles
  • 6th Principle
  • 7th Principle
  • References

3
Biography
  • Pierre Simon Laplace was born in Normandy on
    March 23, 1749, and died at Paris on March 5,
    1827
  • French scientist, mathematician and astronomer
    established mathematically the stability of the
    Solar system and its origin - without a divine
    intervention
  • Professor of mathematics in the École militaire
    of Paris at the age of 19.

4
Biography (Contd)
  • Under Napoleon, Laplace was a member, then
    chancellor, of the Senate, and received the
    Legion of Honour in 1805. Appointed Minister of
    the Interior, in 1799. Removed from office by
    Napoleon after six weeks only!!
  • Named a Marquis in 1817 after the restoration of
    the Bourbons
  • Main publications
  • Mécanique céleste (1771, 1787)
  • Théorie analytique des probabilités 1812 first
    edition dedicated to Napoleon

5
History Of Central Limit Theorem From De Moivre
to Laplace
  • De Moivre investigated the limits of the binomial
    distribution as the number of trials increases
    without bound and found that the function
    exp(-x2) came up in connection with this problem.
  • The formulation of the normal distribution,
    (1/v2)exp(-x2/2), came with Thomas Simpson.

6
History Of CLT (Contd)
  • This idea was was expanded upon by the German
    mathematician Carl Friedrich Gauss who then
    developed the principle of least squares.
  • Independently, the French mathematicians Pierre
    Simon de Laplace and Legendre also developed
    these ideas. It was with Laplace's work that the
    first inklings of the Central Limit Theorem
    appeared.
  • In France, the normal distribution is known as
    Laplacian Distribution while in Germany it is
    known as Gaussian.

7
Derivation of the CLT
  • Initial Work Laplace was calculating the
    probability distribution of the sum of meteor
    inclination angles. He assumed that all the
    angles were r.vs following a triangular
    distribution between 0 and 90 degrees
  • Problems
  • The deviation between the arithmetic mean which
    was inflicted with observational errors, and the
    theoretical value
  • The exact calculation was not achievable due to
    the considerable amount of celestrial bodies
  • Solution Find an approximation !!

8
First Version of the CLT
  • Laplace introduced the m.g.f,
    which is known as Laplace Transform of
    f
  • He then introduced the Characteristic function
  • If is a sample of i.i.d.
    obs.,
  • Assume that we have a discrete r.v. x, that takes
    on the values
  • m, -m1,,0,,m-1,m with prob. p-m ,,pm.
  • Let Sn be the sum of the n possible errors.

9
(No Transcript)
10
CLT for the Binomial Distribution
11
Final Note on The Proof of The CLT
  • It was Lyapunov's analysis that led to the modern
    characteristic function approach to the Central
    Limit Theorem.
  • Where

12
Laplace Bayesian ideasOverview
Philosophical essay on probabilities by Laplace
  • General principles on probability
  • Expectation
  • Analytical methods
  • Applications

13
4th 5th principles conditional marginal give
the joint
Here the question posed by some philosophers
concerning the influence of the past on the
probability of the future, presents itself
14
6th principle discrete Bayes theorem
Fundamental principle of that branch of the
analysis of chance that consists of reasoning a
posteriori from events to causes
15
7th principle probability of future based on
observations
() the correct way of relating past events to
the probability of causes and of future events
()
16
References
  • Laplace, Pierre Simon De. Philosophical essay on
    probabilities.
  • Weatherburn, C.E. A First Course in Mathematical
    Statistics.
Write a Comment
User Comments (0)
About PowerShow.com