Statistical Inference (Oxford Science Publications)

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9780198572268: Statistical Inference (Oxford Science Publications)
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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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Incorporating the latest information on development in the field of statistical inference, this book looks at various approaches to point estimation, hypotheses testing, interval estimation and model building. It concentrates on ideas (rather than comprehensive theorem-proving), contains many exercises, and although it is written at a fairly advanced level, the book employs only the necessary mathematics for a full understanding of the text. For researchers in mathematics, medicine, biology and agriculture needing knowledge of the theory of making inferences from observed data.

About the Author:

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.

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Book Description Oxford University Press, United Kingdom, 2002. Hardback. Condition: New. 2nd ed. Language: English. Brand new Book. 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 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 androbust inference. The increasingly important topics of computationally intensive methods and generalised linear models are also included. In this edition, the material on recent developments has been updated, and additional exercises are included in most chapters. Seller Inventory # LHB9780198572268

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