This edited volume looks at whether it is possible to be more transparent about uncertainty in scientific evidence without undermining public understanding and trust. With contributions from leading experts in the field, this book explores the communication of risk and decision-making in an increasingly post-truth world. Drawing on case studies from climate change to genetic testing, the authors argue for better quality evidence synthesis to cut through the noise and highlight the need for more structured public dialogue. For uncertainty in scientific evidence to be communicated effectively, they conclude that trustworthiness is vital: the data and methods underlying statistics must be transparent, valid, and sound, and the numbers need to demonstrate practical utility and add social value to people’s lives. Presenting a conceptual framework to help navigate the reader through the key social and scientific challenges of a post-truth era, this book will be of great relevance to students, scholars, and policy makers with an interest in risk analysis and communication.

Galligan (Professor Emeritus, English, Western Michigan U.-Kalamazoo) argues that contemporary American critics should embrace literary truths with all of their uncertainties rather than cling to make- believe certainties of ideologies. He celebrates values commonly associated with modern, not postmodern, criticism, applying them to contemporary works in a series of fresh and unusual inquiries. He finds implications for criticism in work from the physical sciences and in the works of largely ignored novelists. Annotation copyrighted by Book News, Inc., Portland, OR

"In Masters of Uncertainty, Phaedra Daipha offers a new framework for understanding decision-making practice after spending years immersed in a northeastern office of the National Weather Service. Arguing that forecasters have made a virtue of the unpredictability of the weather, Daipha shows how they enlist an onmivorous appetite for information and improvisational collage techniques to create a locally meaningful forecast on their computer screens. This richly detailed and lucidly written book advances a theory of decision making that foregrounds the pragmatic and situated nature of expert cognition and casts new light on how we make decisions in the digital age"--Page {4] of cover.

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.

What if we could learn to accept I don't know and embrace the possibility that the future is full of mystery, excitement, and unlimited opportunity? The Art of Uncertainty is an invitation to the reader to consider its essential message: learning to love the unknown by staying present in the moment. If the difficulties of recent years have taught us anything-particularly those who "did everything right" and still saw it all fall apart-it's that none of us has as much control over our lives as we believe. The only thing we can control is our next thought. What if we could learn how to be at peace with uncertainty and embrace the possibility that the future is full of mystery, excitement, and unlimited opportunity? What if we discovered that a new paradigm can be more fulfilling, more rewarding, and more peaceful than what we have known? Living in the I don't know and loving it is an art form we can all master, and The Art of Uncertainty is the perfect guidebook.

Anti-evolutionists, climate denialists, and anti-vaxxers, among others, question some of the best-established scientific findings by referring to the uncertainties in these areas of research. Uncertainty: How It Makes Science Advance shows that uncertainty is an inherent feature of science that makes it advance by motivating further research.

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.