Introduction to Statistical Inference (Paperback, Softcover reprint of the original 1st ed. 1987)

This book is based upon lecture notes developed by Jack Kiefer for a course in statistical inference he taught at Cornell University. The notes were distributed to the class in lieu of a textbook, and the problems were used for homework assignments. Relying only on modest prerequisites of probability theory and cal culus, Kiefer's approach to a first course in statistics is to present the central ideas of the modem mathematical theory with a minimum of fuss and formality. He is able to do this by using a rich mixture of examples, pictures, and math ematical derivations to complement a clear and logical discussion of the important ideas in plain English. The straightforwardness of Kiefer's presentation is remarkable in view of the sophistication and depth of his examination of the major theme: How should an intelligent person formulate a statistical problem and choose a statistical procedure to apply to it? Kiefer's view, in the same spirit as Neyman and Wald, is that one should try to assess the consequences of a statistical choice in some quan titative (frequentist) formulation and ought to choose a course of action that is verifiably optimal (or nearly so) without regard to the perceived "attractiveness" of certain dogmas and methods."

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Springer Texts in Statistics
Release date:	December 2011
First published:	1987
Editors:	Gary Lorden
Authors:	Jack C. Kiefer
Dimensions:	235 x 155 x 18mm (L x W x T)
Format:	Paperback
Pages:	334
Edition:	Softcover reprint of the original 1st ed. 1987
ISBN-13:	978-1-4613-9580-5
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > General
LSN:	1-4613-9580-1
Barcode:	9781461395805

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