Statistical Prediction Analysis (Paperback)

J. Aitchison

ISBN 10: 052129858X / ISBN 13: 9780521298582

Edité par Cambridge University Press, Cambridge, 1980

A propos de cet article

Paperback. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

N° de réf. du vendeur 9780521298582

Détails bibliographiques

• Titre: Statistical Prediction Analysis (Paperback)
• Éditeur: Cambridge University Press, Cambridge
• Date de parution: 1980
• Langue: anglais
• ISBN à 10 chiffres: 052129858X
• ISBN à 13 chiffres: 9780521298582
• Reliure: Paperback
• État de l'article: new

A propos de ce titre

Synopsis

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.

Présentation de l'éditeur

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.