A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935

This is a history of parametric statistical inference, written by one of the most important historians of statistics of the 20th century, Anders Hald. This book can be viewed as a follow-up to his two most recent books, although this current text is much more streamlined and contains new analysis of...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Hald, Anders (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer New York : Imprint: Springer, 2007.
Edición:1st ed. 2007.
Colección:Sources and Studies in the History of Mathematics and Physical Sciences,
Temas:
Probabilities.
Mathematics.
History.
Statistics .
Probability Theory.
History of Mathematical Sciences.
Statistical Theory and Methods.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • The Three Revolutions in Parametric Statistical Inference
  • The Three Revolutions in Parametric Statistical Inference
  • Binomial Statistical Inference
  • James Bernoulli's Law of Large Numbers for the Binomial, 1713, and Its Generalization
  • De Moivre's Normal Approximation to the Binomial, 1733, and Its Generalization
  • Bayes's Posterior Distribution of the Binomial Parameter and His Rule for Inductive Inference, 1764
  • Statistical Inference by Inverse Probability
  • Laplace's Theory of Inverse Probability, 1774-1786
  • A Nonprobabilistic Interlude: The Fitting of Equations to Data, 1750-1805
  • Gauss's Derivation of the Normal Distribution and the Method of Least Squares, 1809
  • Credibility and Confidence Intervals by Laplace and Gauss
  • The Multivariate Posterior Distribution
  • Edgeworth's Genuine Inverse Method and the Equivalence of Inverse and Direct Probability in Large Samples, 1908 and 1909
  • Criticisms of Inverse Probability
  • The Central Limit Theorem and Linear Minimum Variance Estimation by Laplace and Gauss
  • Laplace's Central Limit Theorem and Linear Minimum Variance Estimation
  • Gauss's Theory of Linear Minimum Variance Estimation
  • Error Theory. Skew Distributions. Correlation. Sampling Distributions
  • The Development of a Frequentist Error Theory
  • Skew Distributions and the Method of Moments
  • Normal Correlation and Regression
  • Sampling Distributions Under Normality, 1876-1908
  • The Fisherian Revolution, 1912-1935
  • Fisher's Early Papers, 1912-1921
  • The Revolutionary Paper, 1922
  • Studentization, the F Distribution, and the Analysis of Variance, 1922-1925
  • The Likelihood Function, Ancillarity, and Conditional Inference.

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