Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
  1. Home
  2. Books
  3. Principles of Statistical Inference
  • Cited by 335
Publisher:
Cambridge University Press
Online publication date:
March 2011
Print publication year:
2006
Online ISBN:
9780511813559
DOI:
https://doi.org/10.1017/CBO9780511813559
Subjects:
Life Sciences, Statistical Theory and Methods, Statistics and Probability, Quantitative Biology, Biostatistics and Mathematical Modeling
Information

Book description

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.

Reviews

'A deep and beautifully elegant overview of statistical inference, from one of the towering figures who created modern statistics. This book should be essential reading for all who call themselves ‘statistician’.'

David Hand - Imperial College London

'The explanations of key concepts are written so clearly … that they may be understood even if the mathematical details are skipped.'

Source: MAA Online

'The text is very well written and gives a balanced view of the frequentist and Bayesian notions of probability, without favouring one over the other.'

Source: Journal of Applied Statistics

'… ideally suited for statisticians at all levels who want to refresh their own understanding of the theory of statistical inference without having to wade through theorems and proofs.'

Source: Biometrics

'This is a great book by a great statistician. Buy it and read it.'

Source: Journal of the American Statistical Association

Refine List

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Save to Kindle
  • Save to Dropbox
  • Save to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
Cancel
×

Contents

Contents

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Book summary page views

Total views: 0 *
Loading metrics...

* Views captured on Cambridge Core between #date#. This data will be updated every 24 hours.

Usage data cannot currently be displayed.