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...

* Considers neoclassical models in light of results that can go wrong with them to bring about better models.
* Questions the assumption that markets clear quickly.
* Offers a timely examination of the LTCM collapse.
* Written by a group of well-respected and highly qualified authors.

An integrated approach to fractals and point processes

This publication provides a complete and integrated presentation of the fields of fractals and point processes, from definitions and measures to analysis and estimation. The authors skillfully demonstrate how fractal-based point processes, established as the intersection of these two fields, are tremendously useful for representing and describing a wide variety of diverse phenomena in the physical and biological sciences. Topics range from information-packet arrivals on a computer network to action-potential occurrences in a...

Comparing and contrasting the reality of subjectivity in the work of history's great scientists and the modern Bayesian approach to statistical analysis
Scientists and researchers are taught to analyze their data from an objective point of view, allowing the data to speak for themselves rather than assigning them meaning based on expectations or opinions. But scientists have never behaved fully objectively. Throughout history, some of our greatest scientific minds have relied on intuition, hunches, and personal beliefs to make sense of empirical data-and these subjective influences have...

Nonlinear Bayesian modelling is a relatively new field, but one that has seen a recent explosion of interest. Nonlinear models offer more flexibility than those with linear assumptions, and their implementation has now become much easier due to increases in computational power. Bayesian methods allow for the incorporation of prior information, allowing the user to make coherent inference. Bayesian Methods for Nonlinear Classification and Regression is the first book to bring together, in a consistent statistical framework, the ideas of nonlinear modelling and Bayesian methods.

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The first step-by-step guide to conducting successful Chi-squared tests

Chi-squared testing is one of the most commonly applied statistical techniques. It provides reliable answers for researchers in a wide range of fields, including engineering, manufacturing, finance, agriculture, and medicine.

A Guide to Chi-Squared Testing brings readers up to date on recent innovations and important material previously published only in the former Soviet Union. Its clear, concise treatment and practical advice make this an ideal reference for all researchers and consultants.

The first step-by-step guide to conducting successful Chi-squared tests

Chi-squared testing is one of the most commonly applied statistic...

Offering a viable solution to the long-standing problem of estimating the abundance of rare, clustered populations, adaptive sampling designs are rapidly gaining prominence in the natural and social sciences as well as in other fields with inherently difficult sampling situations. In marked contrast to conventional sampling designs, in which the entire sample of units to be observed is fixed prior to the survey, adaptive sampling strategies allow for increased sampling intensity depending upon observations made during the survey. For example, in a survey to assess the abundance of a rare...

A practical guide to selection, screening, and multiple comparisons

This book addresses experimenters who have knowledge of classical experimental design methodology and expands their repertoire beyond hypothesis testing by providing statistical methods appropriate for selection, screening, and multiple comparisons. It concentrates on three types of procedures: selection procedures that use the "indifference-zone" approach, screening procedures using the "subset" approach, and multiple comparison procedures involving normal means. This is the first book, specifically designed for...