
Statistical Prediction Analysis
Cambridge University Press
Published on 28. February 1980
Book
Paperback/Softback
288 pages
978-0-521-29858-2 (ISBN)
Description
Practitioners of many skills face the need to make some realistic statement about the likely outcome of a future 'experiment of interest' on the basis of observed variability of outcomes in previously conducted related experiments. In this book the authors provide the predictor with the data and formulae which will assist in accurate forecasting, and suggest that an effective answer is to be found in the concept of predictive distribution within the framework of statistical prediction analysis. An applied mathematical approach is adopted throughout and the book is aimed at readers with some statistical knowledge, final year undergraduates, numerate scientists, technologists and medical workers interested in predictive techniques.
Reviews / Votes
'...this is a rare and important textbook. Important because it is the first to address itself to predictivism and rare due to its expository clarity and lucidity and both for the care and effort that went into the work.' Bulletin of the American Mathematical SocietyMore details
Language
English
Place of publication
Cambridge
United Kingdom
Target group
College/higher education
Product notice
Paperback (trade)
Illustrations
Worked examples or Exercises
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 17 mm
Weight
471 gr
ISBN-13
978-0-521-29858-2 (9780521298582)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
J. Aitchison | I. R. Dunsmore
Statistical Prediction Analysis
Book
09/1975
Cambridge University Press
€46.51
Article exhausted; check for reprint
Previous edition
J. Aitchison | I. R. Dunsmore
Statistical Prediction Analysis
Book
09/1975
Cambridge University Press
€46.51
Article exhausted; check for reprint
Content
Preface; 1. Introduction; 2. Predictive distributions; 3. Decisive prediction; 4. Informative prediction; 5. Mean coverage tolerance prediction; 6. Guaranteed coverage tolerance prediction; 7. Other approaches to prediction; 8. Sampling inspection; 9. Regulation and optimisation; 10. Calibration; 11. Diagnosis; 12. Treatment allocation; Appendix; Bibliography; Author Index; Subject Index; Example and problem index.