The Cult Of Statistical Significance

The Cult of Statistical Significance shows, field by field, how "statistical significance," a technique that dominates many sciences, has been a huge mistake. The authors find that researchers in a broad spectrum of fields, from agronomy to zoology, employ testing that doesn't "test" and estimating that doesn't "estimate". The facts will startle the outside reader: how could a group of brilliant scientists wander so far from scientific magnitudes? This study will encourage scientists who want to know how to get the statistical sciences back on track and fulfill their quantitative promise. The book shows for the first time how wide the disaster is, and how bad for science, and it traces the problem to its historical, sociological, and philosophical roots.

“McCloskey and Ziliak have been pushing this very elementary, very correct, very important argument through several articles over several years and for reasons I cannot fathom it is still resisted. If it takes a book to get it across, I hope this book will do it. It ought to.” —Thomas Schelling, Distinguished University Professor, School of Public Policy, University of Maryland, and 2005 Nobel Prize Laureate in Economics “With humor, insight, piercing logic and a nod to history, Ziliak and McCloskey show how economists—and other scientists—suffer from a mass delusion about statistical analysis. The quest for statistical significance that pervades science today is a deeply flawed substitute for thoughtful analysis. . . . Yet few participants in the scientific bureaucracy have been willing to admit what Ziliak and McCloskey make clear: the emperor has no clothes.” —Kenneth Rothman, Professor of Epidemiology, Boston University School of Health The Cult of Statistical Significance shows, field by field, how “statistical significance,” a technique that dominates many sciences, has been a huge mistake. The authors find that researchers in a broad spectrum of fields, from agronomy to zoology, employ “testing” that doesn’t test and “estimating” that doesn’t estimate. The facts will startle the outside reader: how could a group of brilliant scientists wander so far from scientific magnitudes? This study will encourage scientists who want to know how to get the statistical sciences back on track and fulfill their quantitative promise. The book shows for the first time how wide the disaster is, and how bad for science, and it traces the problem to its historical, sociological, and philosophical roots. Stephen T. Ziliak is the author or editor of many articles and two books. He currently lives in Chicago, where he is Professor of Economics at Roosevelt University. Deirdre N. McCloskey, Distinguished Professor of Economics, History, English, and Communication at the University of Illinois at Chicago, is the author of twenty books and three hundred scholarly articles. She has held Guggenheim and National Humanities Fellowships. She is best known for How to Be Human* Though an Economist (University of Michigan Press, 2000) and her most recent book, The Bourgeois Virtues: Ethics for an Age of Commerce (2006).

A witty and thoughtful romp through the profession and practice of economics

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.

A jargon-free introduction for students and researchers looking to interpret the practical significance of their results.

This book explains in layperson's terms a new approach to studying consciousness based on a partnership between neuroscientists and complexity scientists. The author, a physicist turned neuroscientist, outlines essential features of this partnership. The new science goes well beyond traditional cognitive science and simple neural networks, which are often the focus in artificial intelligence research. It involves many fields including neuroscience, artificial intelligence, physics, cognitive science, and psychiatry. What causes autism, schizophrenia, and Alzheimer's disease? How does our unconscious influence our actions? As the author shows, these important questions can be viewed in a new light when neuroscientists and complexity scientists work together. This cross-disciplinary approach also offers fresh insights into the major unsolved challenge of our age: the origin of self-awareness. Do minds emerge from brains? Or is something more involved? Using human social networks as a metaphor, the author explains how brain behavior can be compared with the collective behavior of large-scale global systems. Emergent global systems that interact and form relationships with lower levels of organization and the surrounding environment provide useful models for complex brain functions. By blending lucid explanations with illuminating analogies, this book offers the general reader a window into the latest exciting developments in brain research.

Deirdre Nansen McCloskey's latest meticulous work examines how economics can become a more "human" science. Economic historian Deirdre Nansen McCloskey has distinguished herself through her writing on the Great Enrichment and the betterment of the poor—not just materially but spiritually. In Bettering Humanomics she continues her intellectually playful yet rigorous analysis with a focus on humans rather than the institutions. Going against the grain of contemporary neo-institutional and behavioral economics which privilege observation over understanding, she asserts her vision of “humanomics,” which draws on the work of Bart Wilson, Vernon Smith, and most prominently, Adam Smith. She argues for an economics that uses a comprehensive understanding of human action beyond behaviorism. McCloskey clearly articulates her points of contention with believers in “imperfections,” from Samuelson to Stiglitz, claiming that they have neglected scientific analysis in their haste to diagnose the ills of the system. In an engaging and erudite manner, she reaffirms the global successes of market-tested betterment and calls for empirical investigation that advances from material incentives to an awareness of the human within historical and ethical frameworks. Bettering Humanomics offers a critique of contemporary economics and a proposal for an economics as a better human science.

Elements of Surprise opens with an novel but narrow focus: how a particular cognitive bias, the "curse of knowledge," underwrites stories that rely on what it calls "well-made surprise," as seen in (for example) classic detective fiction--that is, surprises in novels, films, television, and plays that set us up to be fooled in ways we find pleasing and satisfying. But from there, the book expands its reach. At its core, "cursed" thinking underlies almost everything people write, say, and think about both other people and our own pasts. The more information we have about something, and the more experience we have with it, the harder it is to step outside that experience. What unfolds is both a fresh approach to mental heuristics and biases and an ambitious work of cognitive literary criticism. Elements of Surprise provides a new and exciting way of thinking about the mechanics of narrative, explored through thoughtful readings of classic, popular, and obscure texts.--