Operational Subjective Statistical Methods: A Mathematical, Philosophical, And Historical Introduction

The mathematical implications of personal beliefs and values in science and commerce

Amid a worldwide resurgence of interest in subjectivist statistical method, this book offers a fresh look at the role of personal judgments in statistical analysis. Frank Lad demonstrates how philosophical attention to meaning provides a sensible assessment of the prospects and procedures of empirical inferential learning.

Operational Subjective Statistical Methods offers a systematic investigation of Bruno de Finetti's theory of probability and logic of uncertainty, which recognizes probability as the measure of personal uncertainty at the heart of its mathematical presentation. It identifies de Finetti's "fundamental theorem of coherent provision" as the unifying structure of probabilistic logic, and highlights the judgment of exchangeability rather than causal independence as the key probabilistic component of statistical inference.

Broad in scope, yet firmly grounded in mathematical detail, this text/reference

Invites readers to address the subjective personalist meaning of probability as motivating the mathematical construction
* Contains numerous examples and problems, including computing problems using Matlab, assuming no background in Matlab
* Explains how to use the material in three distinct sequential courses in math and statistics, as well as in courses at the graduate level in applied fields
* Provides an introductory basis for understanding more complex structures of statistical analysis


Complete with fifty illustrations, Operational Subjective Statistical Methods makes an intriguing discipline accessible to professionals, students, and the interested general reader. It contains a wealth of teaching and research material, and offers profound insight into the relationship between philosophy, faith, and scientific method.

FRANK LAD, PhD, is Senior Lecturer in Mathematics and Statistics at the University of Canterbury, Christchurch, New Zealand. He has worked on applied statistical problems in demography, economics, and zoology.

Philosophical and Historical Introduction.

Quantities, Prevision, and Coherency.

Coherent Statistical Inference.

Related Forms for Asserting Uncertain Knowledge.

Distribution Functions.

Proper Scoring Rules.

The Multivariate Normal Distribution and Its Mixtures.

Sequential Forecasting Based on Linear Conditional Prevision Structures: Theory and Practice of Linear Regression.

The Direction of Statistical Research.

References.

Index.