Uncertain Chances


Book Description

Maurice Lee's study illustrates how writers such as Poe, Melville, Douglass, Thoreau, Dickinson, and others participated in a broad intellectual and cultural shift in which Americans increasingly learned to live with the threatening and wonderful possibilities of chance.




Risk, Uncertainty and Profit


Book Description

A timeless classic of economic theory that remains fascinating and pertinent today, this is Frank Knight's famous explanation of why perfect competition cannot eliminate profits, the important differences between "risk" and "uncertainty," and the vital role of the entrepreneur in profitmaking. Based on Knight's PhD dissertation, this 1921 work, balancing theory with fact to come to stunning insights, is a distinct pleasure to read. FRANK H. KNIGHT (1885-1972) is considered by some the greatest American scholar of economics of the 20th century. An economics professor at the University of Chicago from 1927 until 1955, he was one of the founders of the Chicago school of economics, which influenced Milton Friedman and George Stigler.




Uncertainty


Book Description

This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance." The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, such as out-of-the-box regression, cannot help in discovering cause. This new way of looking at uncertainty ties together disparate fields — probability, physics, biology, the “soft” sciences, computer science — because each aims at discovering cause (of effects). It broadens the understanding beyond frequentist and Bayesian methods to propose a Third Way of modeling.




Probability and Bayesian Modeling


Book Description

Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus background. The first part of the book provides a broad view of probability including foundations, conditional probability, discrete and continuous distributions, and joint distributions. Statistical inference is presented completely from a Bayesian perspective. The text introduces inference and prediction for a single proportion and a single mean from Normal sampling. After fundamentals of Markov Chain Monte Carlo algorithms are introduced, Bayesian inference is described for hierarchical and regression models including logistic regression. The book presents several case studies motivated by some historical Bayesian studies and the authors’ research. This text reflects modern Bayesian statistical practice. Simulation is introduced in all the probability chapters and extensively used in the Bayesian material to simulate from the posterior and predictive distributions. One chapter describes the basic tenets of Metropolis and Gibbs sampling algorithms; however several chapters introduce the fundamentals of Bayesian inference for conjugate priors to deepen understanding. Strategies for constructing prior distributions are described in situations when one has substantial prior information and for cases where one has weak prior knowledge. One chapter introduces hierarchical Bayesian modeling as a practical way of combining data from different groups. There is an extensive discussion of Bayesian regression models including the construction of informative priors, inference about functions of the parameters of interest, prediction, and model selection. The text uses JAGS (Just Another Gibbs Sampler) as a general-purpose computational method for simulating from posterior distributions for a variety of Bayesian models. An R package ProbBayes is available containing all of the book datasets and special functions for illustrating concepts from the book. A complete solutions manual is available for instructors who adopt the book in the Additional Resources section.




Science and Judgment in Risk Assessment


Book Description

The public depends on competent risk assessment from the federal government and the scientific community to grapple with the threat of pollution. When risk reports turn out to be overblownâ€"or when risks are overlookedâ€"public skepticism abounds. This comprehensive and readable book explores how the U.S. Environmental Protection Agency (EPA) can improve its risk assessment practices, with a focus on implementation of the 1990 Clean Air Act Amendments. With a wealth of detailed information, pertinent examples, and revealing analysis, the volume explores the "default option" and other basic concepts. It offers two views of EPA operations: The first examines how EPA currently assesses exposure to hazardous air pollutants, evaluates the toxicity of a substance, and characterizes the risk to the public. The second, more holistic, view explores how EPA can improve in several critical areas of risk assessment by focusing on cross-cutting themes and incorporating more scientific judgment. This comprehensive volume will be important to the EPA and other agencies, risk managers, environmental advocates, scientists, faculty, students, and concerned individuals.




Reckoning with Risk


Book Description

Are ordinary people able to reason with risk? Detailing case histories and examples, this text presents readers with tools for understanding statistics. In so doing, it encourages us to overcome our innumeracy and empowers us to take responsibility for our own choices.




Understanding Uncertainty


Book Description

A lively and informal introduction to the role of uncertainty and probability in people's lives from an everyday perspective From television game shows and gambling techniques to weather forecasting and the financial markets, virtually every aspect of modern life involves situations in which the outcomes are uncertain and of varying qualities. But as noted statistician Dennis Lindley writes in this distinctive text, "We want you to face up to uncertainty, not hide it away under false concepts, but to understand it and, moreover, to use the recent discoveries so that you can act in the face of uncertainty more sensibly than would have been possible without the skill." Accessibly written at an elementary level, this outstanding text examines uncertainty in various everyday situations and introduces readers to three rules--craftily laid out in the book--that prove uncertainty can be handled with as much confidence as ordinary logic. Combining a concept of utility with probability, the book insightfully demonstrates how uncertainty can be measured and used in everyday life, especially in decision-making and science. With a focus on understanding and using probability calculations, Understanding Uncertainty demystifies probability and: * Explains in straightforward detail the logic of uncertainty, its truths, and its falsehoods * Explores what has been learned in the twentieth century about uncertainty * Provides a logical, sensible method for acting in the face of uncertainty * Presents vignettes of great discoveries made in the twentieth century * Shows readers how to discern if another person--whether a lawyer, politician, scientist, or journalist--is talking sense, posing the right questions, or obtaining sound answers Requiring only a basic understanding of mathematical concepts and operations, Understanding Uncertainty is useful as a text for all students who have probability or statistics as part of their course, even at the most introductory level.




Uncertain Risks Regulated


Book Description

The scientification of politics and the politicisation of science / Michelle Everson and Ellen Vos -- Opening pandora's box : contextualising the precautionary principle in the European Union / Elisabeth Fisher -- Uncertainties in regulating food safety in France / Julien Besanon and Olivier Borraz -- The origins of regulatory uncertainty in the UK food safety regime / Henry Rothstein -- The Dutch regulatory framework for food risk analysis based food law in the Netherlands / Bernd van der Meulen -- Food safety in Poland : standards, procedures and institutions / Aleksander Surdej and Karolina Zurek -- A default-logic model of factfinding for United States regulation of food safety / Vern Walker -- The French regulatory system on GMOs / Christine Noiville -- The UK regulatory system on GMOs : expanding the debate? / Maria Lee -- GMO regulation in the Netherlands : a story of hope, fear and the limits of poldering / Han Somsen -- The Polish regulatory system on GMOs : between EU influence and national nuances / Patrycja Dabrowska -- The regulation of environmental risks of GMOs in the United States / Michael Rodemeyer -- The EU regulatory system on food safety : between trust and safety / Ellen Vos -- The EU regulatory system for GMOs / Greg Shaffer and Mark Pollack -- European regulation of GMOs : thinking about judicial review in the WTO / Joanne Scott -- The Codex Alimentarius Commission and its food safety measures in the light of their new status / Marille matthee -- Three intimate tales of law and science : hope, despair and transcendence / Michelle Everson -- Science, knowledge and uncertainty in eu risk regulation / Marjolein van Asselt, Ellen Vos and Bram Rooijackers -- The role of scientific experts in risk regulation of foods / Harry Kuiper -- Inclusive risk governance through discourse, deliberation and participation / Andreas Klinke -- Sound science in the European and global market : Karl Polanyi in geneva / Christian Joerges.




War and Chance


Book Description

Uncertainty surrounds every major decision in international politics. Yet there is almost always room for reasonable people to disagree about what that uncertainty entails. No one can reliably predict the outbreak of armed conflict, forecast economic recessions, anticipate terrorist attacks, or estimate the countless other risks that shape foreign policy choices. Many scholars and practitioners therefore believe that it is better to keep foreign policy debates focused on the facts - that it is, at best, a waste of time to debate uncertain judgments that will often prove to be wrong. In War and Chance, Jeffrey A. Friedman shows how foreign policy officials often try to avoid the challenge of assessing uncertainty, and argues that this behavior undermines high-stakes decision making. Drawing on an innovative combination of historical and experimental evidence, he explains how foreign policy analysts can assess uncertainty in a manner that is theoretically coherent, empirically meaningful, politically defensible, practically useful, and sometimes logically necessary for making sound choices. Each of these claims contradicts widespread skepticism about the value of probabilistic reasoning in international politics, and shows how placing greater emphasis on assessing uncertainty can improve nearly any foreign policy debate. A clear-eyed examination of the logic, psychology, and politics of assessing uncertainty, War and Chance provides scholars and practitioners with new foundations for understanding one of the most controversial elements of foreign policy discourse.




Risk Intelligence


Book Description

We must make judgments all the time when we can't be certain of the risks. Should we have that elective surgery? Trust the advice of our financial adviser? Take that new job we've been offered? How worried should we be about terrorist attacks? In this lively and groundbreaking book, pioneering researcher Dylan Evans introduces a newly discovered kind of intelligence for assessing risks, demonstrating how vital this risk intelligence is in our lives and how we can all raise our RQs in order to make better decisions every day. Evans has spearheaded the study of risk intelligence, devising a simple test to measure a person's RQ which when posted online sparked a storm of interest and was taken by tens of thousands of people. His research has revealed that risk intelligence is quite different from IQ, and that the vast majority of us have quite poor risk intelligence. However, he did find some people who have very high RQs. So what makes the difference? Introducing a wealth of fascinating research findings, Evans identifies a key set of common errors in our thinking that most of us fall victim to and that undermine our risk intelligence, such as "ambiguity aversion," overconfidence in our knowledge, the fallacy of mind reading, and our attraction to worst-case scenarios. We are also regularly led astray by the ways in which information is provided to us. Citing a wide range of real-life examples--from the brilliant risk assessment skills of horse race handicappers to the tragically flawed evaluations of risk that caused the financial crisis--Evans illustrates that sometimes our most trusted advisors, including the experts and analysts at the top of their disciplines, don't always give us the best advice when it comes to risk evaluation. Presenting his revolutionary test that allows readers to evaluate their own RQs, Evans introduces a number of simple techniques we can use to build our risk assessment powers and reports on the striking results he's seen in training people to develop their RQs. Both highly engaging and truly mind-changing, Risk Intelligence will fascinate all of those who are interested in how we can improve our thinking in order to enhance our lives.