A History of Inverse Probability (eBook, PDF)
From Thomas Bayes to Karl Pearson
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It is thought as necessary to write a Preface before a Book, as it is judged civil, when you invite a Friend to Dinner, to proffer him a Glass of Hock beforehand for a Whet. John Arbuthnot, from the preface to his translation of Huygens's "De Ratiociniis in Ludo Alooe". Prompted by an awareness of the importance of Bayesian ideas in modern statistical theory and practice, I decided some years ago to undertake a study of the development and growth of such ideas. At the time it seemed appropriate to begin such an investigation with an examination of Bayes's Essay towards solving a problem in the...
It is thought as necessary to write a Preface before a Book, as it is judged civil, when you invite a Friend to Dinner, to proffer him a Glass of Hock beforehand for a Whet. John Arbuthnot, from the preface to his translation of Huygens's "De Ratiociniis in Ludo Alooe". Prompted by an awareness of the importance of Bayesian ideas in modern statistical theory and practice, I decided some years ago to undertake a study of the development and growth of such ideas. At the time it seemed appropriate to begin such an investigation with an examination of Bayes's Essay towards solving a problem in the doctrine of chances and Laplace's Theorie analytique des probabilites, and then to pass swiftly on to a brief consideration of other nineteenth century works before turning to what would be the main topic of the treatise, videlicet the rise of Bayesian statis tics from the 1950's to the present day. It soon became apparent, however, that the amount of Bayesian work published was such that a thorough investigation of the topic up to the 1980's would require several volumes - and also run the risk of incurring the wrath of extant authors whose writings would no doubt be misrepre sented, or at least be so described. It seemed wise, therefore, to restrict the period and the subject under study in some way, and I decided to con centrate my attention on inverse probability from Thomas Bayes to Karl Pearson.
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