A History of Parametric Statistical Inference from Bernoulli by Anders Hald

By Anders Hald

This ebook deals an in depth background of parametric statistical inference. overlaying the interval among James Bernoulli and R.A. Fisher, it examines: binomial statistical inference; statistical inference via inverse chance; the relevant restrict theorem and linear minimal variance estimation through Laplace and Gauss; errors concept, skew distributions, correlation, sampling distributions; and the Fisherian Revolution. full of life biographical sketches of a number of the major characters are featured all through, together with Laplace, Gauss, Edgeworth, Fisher, and Karl Pearson. additionally tested are the jobs performed by way of DeMoivre, James Bernoulli, and Lagrange.

Show description

Read Online or Download A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935 (Sources and Studies in the History of Mathematics and Physical Sciences) PDF

Similar probability & statistics books

Matrix Algebra: Exercises and Solutions

This booklet includes over three hundred routines and suggestions that jointly disguise a large choice of subject matters in matrix algebra. they are often used for self sufficient research or in making a difficult and stimulating atmosphere that encourages lively engagement within the studying approach. The needful historical past is a few prior publicity to matrix algebra of the type acquired in a primary direction.

Statistics for Social Data Analysis, 4th Edition

The fourth variation of facts FOR SOCIAL facts research maintains to teach scholars easy methods to practice statistical the way to resolution study questions in a variety of fields. through the textual content, the authors underscore the significance of formulating substantive hypotheses earlier than trying to research quantitative info.

Introduction to General and Generalized Linear Models (Chapman & Hall/CRC Texts in Statistical Science)

Bridging the distance among thought and perform for contemporary statistical version development, creation to basic and Generalized Linear types offers likelihood-based suggestions for statistical modelling utilizing a number of forms of info. Implementations utilizing R are supplied during the textual content, even though different software program programs also are mentioned.

Additional info for A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935 (Sources and Studies in the History of Mathematics and Physical Sciences)

Example text

He seems to have led a quiet life, mainly occupied with his scholarly interests, beginning with theology, moving to mathematics and the natural sciences, and ending with statistical inference. He was elected a Fellow of the Royal Society in 1742. When Bayes died in 1761 his relatives asked Richard Price (1723—1791), another Presbyterian minister, to examine the mathematical papers left by Bayes. Price found a paper on Stirling’s formula and the paper “An Essay Towards Solving a Problem in the Doctrine of Chances,” which he got published in two parts in the Phil.

A fifth volume was published in 1825 [163]. After having completed his astronomical work in 1805, he resumed work on probability and statistics and published the Théorie Analytique des Probabilités (TAP), [159], the most influential book on probability and statistics ever written. In [160] he added the Essai Philosophique sur les Probabilités as a popular introduction to the second edition of the TAP. The Essay was also published separately and he kept on revising and enlarging it until the sixth edition.

Thomas Simpson (1710—1761), [237], had derived the sampling distribution of the mean for observations from a symmetric triangular distribution, a rather complicated function, and had shown numerically that P (|x| < k) > P (|x1 | < k) for 42 5 Laplace’s Theory of Inverse Probability n = 6 and two values of k, from which he concluded that it is advantageous to use the mean as the estimate of . As a first step Laplace [148] introduces a new error distribution with infinite support, the double exponential distribution f (x|, m) = m m|x| e , 4 < x < 4, 4 <  < 4, 0 < m < 4.

Download PDF sample

Rated 4.70 of 5 – based on 5 votes