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

Author:   Anders Hald
Publisher:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of hardcover 1st ed. 2007
ISBN:  

9781441923639


Pages:   225
Publication Date:   19 November 2010
Format:   Paperback
Availability:   Out of print, replaced by POD   Availability explained
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A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935


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Author:   Anders Hald
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of hardcover 1st ed. 2007
Dimensions:   Width: 15.50cm , Height: 1.20cm , Length: 23.50cm
Weight:   0.454kg
ISBN:  

9781441923639


ISBN 10:   1441923632
Pages:   225
Publication Date:   19 November 2010
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of print, replaced by POD   Availability explained
We will order this item for you from a manufatured on demand supplier.

Table of Contents

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.

Reviews

From the reviews: In this very enjoyable and interesting book, Hald ! presents his subject in a very lively style; many ideas and developments in statistics are treated with great clarity. It is very suitable as a course resource in history of statistical inference ! . Throughout, the author provides brief biographical sketches of researchers whose contributions to statistics are included here. ! A very useful and valuable work on the history of statistical inference. ! Summing Up: Highly recommended. Lower- and upper-division undergraduates through faculty. (D. V. Chopra, CHOICE, Vol. 44 (11), July, 2007) This is a useful account of the historical development of the theory that underlies the empirically observed stability of data averages for large samples and how their precision may be measured. ! The resultant book is a suitable text for a one-semester course on what is arguably the core piece of statistical history. (C. C. Heyde, SIAM Review, Vol. 50 (1), 2008)


From the reviews: In this very enjoyable and interesting book, Hald ... presents his subject in a very lively style; many ideas and developments in statistics are treated with great clarity. It is very suitable as a course resource in history of statistical inference ... . Throughout, the author provides brief biographical sketches of researchers whose contributions to statistics are included here. ... A very useful and valuable work on the history of statistical inference. ... Summing Up: Highly recommended. Lower- and upper-division undergraduates through faculty. (D. V. Chopra, CHOICE, Vol. 44 (11), July, 2007) This is a useful account of the historical development of the theory that underlies the empirically observed stability of data averages for large samples and how their precision may be measured. ... The resultant book is a suitable text for a one-semester course on what is arguably the core piece of statistical history. (C. C. Heyde, SIAM Review, Vol. 50 (1), 2008)


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