This 164-page book assembles and updates introductory white papers that have been available on our website. There are substantial new sections, including a 50-page glossary of terms, and two new chapters.
Paul Green (Professor Emeritus of Marketing, University of Pennsylvania) and the "father of conjoint analysis" wrote the foreword for Getting Started with Conjoint Analysis. He writes: "Getting Started with Conjoint Analysis is a practical no-nonsense guide to what happens when one designs, executes, and analyzes data from real marketplace problems. It should appeal to academics and consultant-practitioners alike. The book is easy to follow, while at the same time being almost encyclopedic in its coverage of topics ranging from study design to the presentation of results to clients."

This book defends the view that any adequate account of rational decision making must take a decision maker's beliefs about causal relations into account. The early chapters of the book introduce the nonspecialist to the rudiments of expected utility theory. The major technical advance offered by the book is a "representation theorem" that shows that both causal decision theory and its main rival, Richard Jeffrey's logic of decision, are both instances of a more general conditional decision theory. In providing the most complete and robust defense of causal decision theory the book will be of interest to a broad range of readers in philosophy, economics, psychology, mathematics, and artificial intelligence.

The Bayesian revolution in statistics - where statistics is integrated with decision making in areas such as management, public policy, engineering, and clinical medicine - is here to stay. Introduction to Statistical Decision Theory states the case and in a self-contained, comprehensive way shows how the approach is operational and relevant for real-world decision making under uncertainty.Starting with an extensive account of the foundations of decision theory, the authors develop the intertwining concepts of subjective probability and utility. They then systematically and comprehensively examine the Bernoulli, Poisson, and Normal (univariate and multivariate) data generating processes. For each process they consider how prior judgments about the uncertain parameters of the process are modified given the results of statistical sampling, and they investigate typical decision problems in which the main sources of uncertainty are the population parameters. They also discuss the value of sampling information and optimal sample sizes given sampling costs and the economics of the terminal decision problems.Unlike most introductory texts in statistics, Introduction to Statistical Decision Theory integrates statistical inference with decision making and discusses real-world actions involving economic payoffs and risks. After developing the rationale and demonstrating the power and relevance of the subjective, decision approach, the text also examines and critiques the limitations of the objective, classical approach.

Gilboa and Schmeidler provide a new paradigm for modeling decision making under uncertainty. Case-based decision theory suggests that people make decisions by analogies to past cases: they tend to choose acts that performed well in the past in similar situations, and to avoid acts that performed poorly. The authors describe the general theory and its relationship to planning, repeated choice problems, inductive inference, and learning. They highlight its mathematical and philosophical foundations and compare it to expected utility theory as well as to rule-based systems.
^^^^^^^^^^^^^^^^^^^^^^^
Dimensions: 216 x 138 mm
Weight: 0.27 kg
Manufactured on demand: supplied direct from the printer

In The Mind within the Brain, David Redish brings together cutting edge research in psychology, robotics, economics, neuroscience, and the new fields of neuroeconomics and computational psychiatry, to offer a unified theory of human decision-making. Most importantly, Redish shows how vulnerabilities, or "failure-modes," in the decision-making system can lead to serious dysfunctions, such as irrational behavior, addictions, problem gambling, and PTSD. Told with verve and humor in an easily readable style, Redish makes these difficult concepts understandable. Ranging widely from the surprising roles of emotion, habit, and narrative in decision-making, to the larger philosophical questions of how mind and brain are related, what makes us human, the nature of morality, free will, and the conundrum of robotics and consciousness, The Mind within the Brain offers fresh insight into one of the most complex aspects of human behavior.