Statistical Inference
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.
1100633484
Statistical Inference
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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Statistical Inference

Statistical Inference

Statistical Inference

Statistical Inference

Hardcover(2ND)

$170.00 
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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.

Product Details

ISBN-13: 9780198572268
Publisher: Oxford University Press
Publication date: 08/29/2002
Series: Oxford Science Publications
Edition description: 2ND
Pages: 342
Product dimensions: 9.44(w) x 6.06(h) x 0.90(d)

About the Author

Department of Statistics, Open University

University of Aberdeen

GlaxoSmithKline, Harlow

Table of Contents

1. Introduction2. Properties of estimators3. Maximum likelihood and other methods of estimation4. Hypothesis testing5. Interval estimation6. The decision theory approach to inference7. Bayesian inference8. Non-parametric and robust inference9. Computationally intensive methods10. Generalised linear models
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