Logic Of Statistical Inference
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Logic of Statistical Inference
Author: Ian Hacking
language: en
Publisher: Cambridge University Press
Release Date: 2016-08-26
This book showcases Ian Hacking's early ideas on the central issues surrounding statistical reasoning. Presented in a fresh twenty-first-century series livery, and with a specially commissioned new preface, this influential work is now available for a new generation of readers in statistics, philosophy of science and philosophy of maths.
Principles of Statistical Inference
Author: D. R. Cox
language: en
Publisher: Cambridge University Press
Release Date: 2006-08-10
In this definitive book, D. R. 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.
Your Statistical Consultant
How do you bridge the gap between what you learned in your statistics course and the questions you want to answer in your real-world research? Oriented towards distinct questions in a "How do I?" or "When should I?" format, Your Statistical Consultant is the equivalent of the expert colleague down the hall who fields questions about describing, explaining, and making recommendations regarding thorny or confusing statistical issues. The book serves as a compendium of statistical knowledge, both theoretical and applied, that addresses the questions most frequently asked by students, researchers and instructors. Written to be responsive to a wide range of inquiries and levels of expertise, the book is flexibly organized so readers can either read it sequentially or turn directly to the sections that correspond to their concerns.