Statistical Prediction Analysis

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.

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.