Statistical Inference / Edition 2

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Overview

Adopting a broad view of statistical inference, the text concentrates on what various techniques do, with mathematical proof kept to a minimum. The approach is rigorous but accessible to final year undergraduates. Classical approaches to point estimation, hypothesis testing and interval estimation are all covered thoroughly with recent developments outlined. Separate chapters are devoted to Bayesian inference, to decision theory and to non-parametric and robust inference. The increasingly important topics of computationally intensive methods and generalized linear models are also included. In this edition, the material on recent developments has been updated, and additional exercises are included in most chapters.

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Product Details

  • ISBN-13: 9780198572268
  • Publisher: Oxford University Press, USA
  • Publication date: 6/28/2002
  • Series: Oxford Science Publications
  • Edition description: 2ND
  • Edition number: 2
  • Pages: 352
  • Product dimensions: 9.30 (w) x 6.00 (h) x 0.90 (d)

Meet the Author

Department of Statistics, Open University

University of Aberdeen

GlaxoSmithKline, Harlow

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Table of Contents

1 Introduction 1
2 Properties of estimators 7
3 Maximum likelihood and other methods of estimation 40
4 Hypothesis testing 71
5 Interval estimation 97
6 The decision-theory approach to inference 114
7 Bayesian inference 151
8 Non-parametric and robust inference 185
9 Computationally intensive methods 217
10 Generalized linear models 265
Bibliography 308
Index 319
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