Features
Presents large collections of paradoxes in the sciences and statistics
Provides broad and interesting applications of paradoxes
Offers a new, effective way of learning scientific inference
Analyzes controversies in statistical measures of scientific evidence
Discusses principles and the conceptual unification of statistical paradigms
Develops new architectures for creating artificial intelligent agents
Includes a quick study guide and exercises in each chapter

Summary
Paradoxes are poems of science and philosophy that collectively allow us to address broad multidisciplinary issues within a microcosm. A true paradox is a source of creativity and a concise expression that delivers a profound idea and provokes a wild and endless imagination. The study of paradoxes leads to ultimate clarity and, at the same time, indisputably challenges your mind.

Paradoxes in Scientific Inference analyzes paradoxes from many different perspectives: statistics, mathematics, philosophy, science, artificial intelligence, and more. The book elaborates on findings and reaches new and exciting conclusions. It challenges your knowledge, intuition, and conventional wisdom, compelling you to adjust your way of thinking. Ultimately, you will learn effective scientific inference through studying the paradoxes

Table of Contents
The Joy of Paradoxes: A Random Walk
Introduction to Paradox
Applications of Paradoxes
Mathematical Paradox
Probabilistic and Statistical Paradoxes

Mathematical and Plausible Reasoning
Probability and Randomness
Mathematical Logic and Formal Reasoning
Plausible Reasoning

Statistical Measures of Scientific Evidence
Introduction to Statistical Methods
Statistical Principles
Decision Theory Approach
Controversies in Evidence Measures
Causal Space Theory: Unification of Paradigms
Multiplicity: The Black Hole of Scientific Discovery
Scientific Principles and Inferences
Epistemology
Controversies in Scientific Philosophy
Paradox of a Logical System
Paradox and Game Theory

Artificial Intelligence
Paradoxes in Artificial Intelligence
Architecture of Artificial Intelligent Agent
Learning and Teaching

Appendix: Mathematical Notations

Bibliography

Index