- Année : 2006
- Éditeur : Cambridge University Press

- Pages : XV-219
- Support : Print
- Edition : Original
- Ville : Cambridge
- ISBN : 0521685672 (pbk.)
- URL : Lien externe
- Date de création : 17-05-2012
- Dernière mise à jour : 17-05-2012

In this definitive book, David Roxbee Cox gives a comprehensive and balanced appraisal of statistical inference. He develops the key concepts, describing and comparing the main ideas and controversies over foundational issues that have been keenly argued for more than two-hundred years. Continuing a sixty-year career of major contributions to statistical thought, no one is better placed to give this much-needed account of the field. An appendix gives a more personal assessment of the merits of different ideas. The content ranges from the traditional to the contemporary. While specific applications are not treated, the book is strongly motivated by applications across the sciences and associated technologies. The mathematics is kept as elementary as feasible, though previous knowledge of statistics is assumed. The book will be valued by every user or student of statistics who is serious about understanding the uncertainty inherent in conclusions from statistical analyses. – Contents : – Preface. – 1. Preliminaries; – 2. Some concepts and simple applications; – 3. Significance tests; – 4. More complicated situations; – 5. Some interpretational issues; – 6. Asymptotic theory; – 7. Further aspects of maximum likelihood; – 8. Additional objectives; – 9. Randomization-based analysis. – Appendix A. A brief history; – Appendix B. A personal view. – Includes bibliographical references (p. 201-208) and indexes.

In this definitive book, David Roxbee Cox gives a comprehensive and balanced appraisal of statistical inference. He develops the key concepts, describing and comparing the main ideas and controversies over foundational issues that have been keenly argued for more than two-hundred years. Continuing a sixty-year career of major contributions to statistical thought, no one is better placed to give this much-needed account of the field. An appendix gives a more personal assessment of the merits of different ideas. The content ranges from the traditional to the contemporary. While specific applications are not treated, the book is strongly motivated by applications across the sciences and associated technologies. The mathematics is kept as elementary as feasible, though previous knowledge of statistics is assumed. The book will be valued by every user or student of statistics who is serious about understanding the uncertainty inherent in conclusions from statistical analyses. – Contents : – Preface. – 1. Preliminaries; – 2. Some concepts and simple applications; – 3. Significance tests; – 4. More complicated situations; – 5. Some interpretational issues; – 6. Asymptotic theory; – 7. Further aspects of maximum likelihood; – 8. Additional objectives; – 9. Randomization-based analysis. – Appendix A. A brief history; – Appendix B. A personal view. – Includes bibliographical references (p. 201-208) and indexes.