Statistical Inference

Hardcover | June 15, 2002

byPaul Garthwaite, Ian Jolliffe, Byron Jones

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Adopting a broad view of statistical inference, this text concentrates on what various techniques do, with mathematical proofs kept to a minimum. The approach is rigorous, but will be accessible to final year undergraduates. Classical approaches to point estimation, hypothesis testing andinterval 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 generalised linear modelsare 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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Adopting a broad view of statistical inference, this text concentrates on what various techniques do, with mathematical proofs kept to a minimum. The approach is rigorous, but will be accessible to final year undergraduates. Classical approaches to point estimation, hypothesis testing andinterval estimation are all covered thoroughly, ...

Paul Garthwaite is in the Department of Statistics, Open University, UK. Ian Jolliffe is a Professor of Statistics, University of Aberdeen. Byron Jones is a Director, Research Statistics Unit, GlaxoSmithKline, UK.
Format:HardcoverDimensions:352 pages, 9.21 × 6.14 × 0.93 inPublished:June 15, 2002Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0198572263

ISBN - 13:9780198572268

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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