Introduction to Statistical Inference

  • Authors
  • Jack Carl Kiefer
  • Gary Lorden

Part of the Springer Texts in Statistics book series (STS)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Jack Carl Kiefer
    Pages 1-3
  3. Jack Carl Kiefer
    Pages 4-22
  4. Jack Carl Kiefer
    Pages 23-30
  5. Jack Carl Kiefer
    Pages 31-80
  6. Jack Carl Kiefer
    Pages 81-136
  7. Jack Carl Kiefer
    Pages 137-157
  8. Jack Carl Kiefer
    Pages 158-245
  9. Jack Carl Kiefer
    Pages 246-286
  10. Jack Carl Kiefer
    Pages 287-311
  11. Back Matter
    Pages 312-334

About this book

Introduction

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.

Keywords

Likelihood Mathematica Statistica Variance class derivation equality form geometry minimum presentation probability statistical inference statistics testing

Editors and affiliations

  • Gary Lorden
    • 1
  1. 1.California Institute of TechnologyPasadenaUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4613-9578-2
  • Copyright Information Springer-Verlag New York 1987
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-9580-5
  • Online ISBN 978-1-4613-9578-2
  • Series Print ISSN 1431-875X
  • About this book