Praise for the First Edition

"This...novel and highly stimulating book, which emphasizes solving real problems...should be widely read. It will have a positive and lasting effect on the teaching of modeling and statistics in general." - Short Book Reviews

This new edition features developments and real-world examples that showcase essential empirical modeling techniques

Successful empirical model building is founded on the relationship between data and approximate representations of the real systems that generated that data. As a result, it is essential for researchers who construct these models to possess the special skills and techniques for producing results that are insightful, reliable, and useful. "Empirical Model Building: Data, Models, and Reality, Second Edition" presents a hands-on approach to the basic principles of empirical model building through a shrewd mixture of differential equations, computer-intensive methods, and data. The book outlines both classical and new approaches and incorporates numerous real-world statistical problems that illustrate modeling approaches that are applicable to a broad range of audiences, including applied statisticians and practicing engineers and scientists.

The book continues to review models of growth and decay, systems where competition and interaction add to the complextiy of the model while discussing both classical and non-classical data analysis methods. This Second Edition now features further coverage of momentum based investing practices and resampling techniques, showcasing their importance and expediency in the real world. The author provides applications of empirical modeling, such as computer modeling of the AIDS epidemic to explain why North America has most of the AIDS cases in the First World and data-based strategies that allow individual investors to build their own investment portfolios. Throughout the book, computer-based analysis is emphasized and newly added and updated exercises allow readers to test their comprehension of the presented material.

"Empirical Model Building, Second Edition" is a suitable book for modeling courses at the upper-undergraduate and graduate levels. It is also an excellent reference for applied statisticians and researchers who carry out quantitative modeling in their everyday work.

Expert guidance and step-by-step instruction for building a successful diversity, equity, and inclusion initiative from scratch In Diversity and Inclusion Matters: Tactics and Tools to Inspire Equity and Game-Changing Performance, award-winning diversity, equity, and inclusion (DE&I) expert Jason R. Thompson delivers a practical and engaging handbook for implementing a DE&I program in your organization. The CAPE technique, developed by the author, gives you a clear blueprint and the tools you'll need to make your diversity program a success. In this book, you'll learn how to achieve early and significant wins to create the necessary and long term organizational change needed for successful DE&I programs. Find out what data you need to collect, how to analyze it, and choose the right goals for your organization. In addition, the CAPE technique will show your progress and ROI. You will learn to: Manage and lead a diversity council and implement diversity initiatives in the correct order Get early buy-in and long-term commitment from a Chief Executive Officer by knowing what to ask for and when Set appropriate and realistic expectations for a DE&I program with the executive leadership team Perfect for diversity and inclusion professionals, human resources leaders, founders, business owners, and executives, Diversity and Inclusion Matters will also earn a place in the libraries of students of human resources, leadership, management, and finance.

While the common practice of Quality Assurance aims to prevent bad units from being shipped beyond some allowable proportion, statistical process control (SPC) ensures that bad units are not created in the first place. Its philosophy of continuous quality improvement, to a great extent responsible for the success of Japanese manufacturing, is rooted in a paradigm as process-oriented as physics, yet produces a friendly and fulfilling work environment. The first edition of this groundbreaking text showed that the SPC paradigm of W. Edwards Deming was not at all the same as the Quality Control paradigm that has dominated American manufacturing since World War II. Statistical Process Control: The Deming Paradigm and Beyond, Second Edition reveals even more of Deming's philosophy and provides more techniques for use at the managerial level. Explaining that CEOs and service industries need SPC at least as much as production managers, it offers precise methods and guidelines for their use. Using the practical experience of the authors working both in America and Europe, this book shows how SPC can be implemented in a variety of settings, from health care to manufacturing. It also provides you with the necessary technical background through mathematical and statistical appendices. According to the authors, companies with managers who have adopted the philosophy of statistical process control tend to survive. Those with managers who do not are likely to fail. In which group will your company be?

While the common practice of Quality Assurance aims to prevent bad units from being shipped beyond some allowable proportion, statistical process control (SPC) ensures that bad units are not created in the first place. Its philosophy of continuous quality improvement, to a great extent responsible for the success of Japanese manufacturing, is rooted in a paradigm as process-oriented as physics, yet produces a friendly and fulfilling work environment.

The first edition of this groundbreaking text showed that the SPC paradigm of W. Edwards Deming was not at all the same as the Quality Control paradigm that has dominated American manufacturing since World War II. Statistical Process Control: The Deming Paradigm and Beyond, Second Edition reveals even more of Deming's philosophy and provides more techniques for use at the managerial level. Explaining that CEOs and service industries need SPC at least as much as production managers, it offers precise methods and guidelines for their use.

Using the practical experience of the authors working both in America and Europe, this book shows how SPC can be implemented in a variety of settings, from health care to manufacturing. It also provides you with the necessary technical background through mathematical and statistical appendices. According to the authors, companies with managers who have adopted the philosophy of statistical process control tend to survive. Those with managers who do not are likely to fail. In which group will your company be?

A unique, integrated treatment of computer modeling and simulation "The future of science belongs to those willing to make the shift to simulation-based modeling," predicts Rice Professor James Thompson, a leading modeler and computational statistician widely known for his original ideas and engaging style. He discusses methods, available to anyone with a fast desktop computer, for integrating simulation into the modeling process in order to create meaningful models of real phenomena. Drawing from a wealth of experience, he gives examples from trading markets, oncology, epidemiology, statistical process control, physics, public policy, combat, real-world optimization, Bayesian analyses, and population dynamics. Dr. Thompson believes that, so far from liberating us from the necessity of modeling, the fast computer enables us to engage in realistic models of processes in , for example, economics, which have not been possible earlier because simple stochastic models in the forward temporal direction generally become quite unmanageably complex when one is looking for such things as likelihoods. Thompson shows how simulation may be used to bypass the necessity of obtaining likelihood functions or moment-generating functions as a precursor to parameter estimation. Simulation: A Modeler’s Approach is a provocative and practical guide for professionals in applied statistics as well as engineers, scientists, computer scientists, financial analysts, and anyone with an interest in the synergy between data, models, and the digital computer.

This book is the product of many years' experience teaching behavioral science in a way that demonstrates its relevance to clinical medicine. We have been guided by the reactions and evaluations of many first-year medical students. The result is a conceptual framework different from those that we and others had tried before. Because the clinical relevance of knowledge about human behavior is less apparent to many first-year students than that of the other traditional pre clinical courses, books and courses organized as brief introductions to psychology, sociology, and behavioral neurology have often been poorly received. Various medical schools and texts have explored ways to overcome this difficulty. One text organizes the presentation around very practical problems which are of unmistakable interest to the future physician: the therapeutic relationship, death and dying, sexuality, and pain, to give a few examples. Another emphasizes stages of development, periods of the human life cycle, as its organizing principle. Both of these approaches have merit and have been used successfully in various schools. They seem to us, however, to have a potentially serious shortcoming. They focus student attention too much on the more immediately intriguing issues of specific clinical problems or on the more easily recognized age specific behavioral issues. In the limited time available, the teaching of general principles of human behavioral functioning may then be neglected."

This is a new release of the original 1930 edition.

From the wilderness of Minnesota comes a moving story about a magnificent animal that was born as a result of a union between a beautiful female German Shepherd and an alpha male timber wolf. Filled with action, suspense, and a heart-filled conclusion, From the Wilderness is somewhat reminiscent of Call of the Wild and White Fang, and is written for readers of all ages.

A uniquely timely look at where modern financial economic theory has failed–and where we should go from here

The collapse of the Scholes-Merton based Long Term Capital Management (LTCM) hedge fund should have sounded alarms or, at least, raised questions about investment strategies based on risk-neutral probabilities. More recently, the fallout of Enron, WorldCom, and similar fiascos must now give pause to those who take the efficient market-based formula for "fair prices" (especially in options and derivatives) as rigid laws.

This provocative volume provides a new, antiefficient markets approach to investment theory and management. Questioning the assumption that markets clear neatly and quickly, Models for Investors in Real World Markets considers neoclassical models in light of what can go wrong with them, outlines basic institutional factors associated with how stock markets operate, and then offers ways to bring about better (though never correct) models. Providing a stinging critique of modern financial economic theory, this timely book:

• Introduces basic concepts of utility theory, the cornerstone of portfolio theory
• Illustrates why diversification is an important fundamental requirement of rational investment choice
• Provides a detailed procedure for analyzing securities, borrowing the concepts of Benjamin Graham and David Dodd, and building a quantitative framework for them
• Examines the importance of compound interest and observes that stock growth may be viewed as noisy compound interest
• Demonstrates that options are themselves stochastic, risky entities and not magical devices for the elimination of risk
• Develops a conceptualization of risk profiling based on their development of the simugram. As opposed to the Markowitz approach of maximizing growth subject to acceptable levels of volatility, the authors use the simugram, their computer intensive forecast of the time-indexed density function of portfolio value. Percentiles, rather than expectations, form the major bases for the criterion functions and constraints utilized for portfolio management.

For anyone who has ever questioned–or should have questioned–the efficient market orthodoxy, this book will be a valuable reference on market analysis and investment strategy.