Causation is at once familiar and mysterious. Many believe that the causal relation is not directly observable, but that we nevertheless can somehow detect its presence in the world. Common sense seems to have a firm grip on causation, and much work in the natural and social sciences relies on the idea. Yet neither common sense nor extensive philosophical debate has led us to anything like agreement on the correct analysis of the concept of causation, or an account of the metaphysical nature of the causal relation. Contemporary debates are driven by opposing motivations, conflicting intuitions, and unarticulated methodological assumptions. Causation: A User's Guide cuts a clear path through this confusing but vital landscape. L. A. Paul and Ned Hall guide the reader through the most important philosophical treatments of causation, negotiating the terrain by taking a set of examples as landmarks. Special attention is given to counterfactual and related analyses of causation. Using a methodological principle based on the close examination of potential counterexamples, they clarify the central themes of the debate about causation, and cover questions about causation involving omissions or absences, preemption and other species of redundant causation, and the possibility that causation is not transitive. Along the way, Paul and Hall examine several contemporary proposals for analyzing the nature of causation and assess their merits and overall methodological cogency. The book is designed to be of value both to trained specialists and those coming to the problem of causation for the first time. It provides the reader with a broad and sophisticated view of the metaphysics of the causal relation.
Causation is at once familiar and mysterious—we can detect its presence in the world, but we cannot agree on the metaphysics of the causal relation. L. A. Paul and Ned Hall guide the reader through the most important philosophical treatments of causation, and develop a broad and sophisticated understanding of the issues under debate.
Crossing the road, we look both ways. Riding a bicycle at night, we use lights. So why is our attitude towards online security so relaxed? Edward Lucas reveals the ways in which cyberspace is not the secure zone we may hope, how passwords provide no significant obstacle to anyone intent on getting past them, and how anonymity is easily accessible to anyone – malign or benign – willing to take a little time covering their tracks. The internet was designed by a small group of computer scientists looking for a way to share information quickly. In the last twenty years it has expanded rapidly to become a global information superhighway, available to all comers, but also wide open to those seeking invisibility. This potential for anonymity means neither privacy nor secrecy are really possible for law-abiding corporations or citizens. As identities can be faked so easily the very foundations on which our political, legal and economic systems are based are vulnerable. Businesses, governments, national security organisations and even ordinary individuals are constantly at risk and with our ever increasing dependence on the internet and smart-phone technology this threat is unlikely to diminish – in fact, the target for cyber-criminals is expanding all the time. Not only does Cyberphobia lay bare the dangers of the internet, it also explores the most successful defensive cyber-strategies, options for tracking down transgressors and argues that we are moving into a post-digital age where once again face-to-face communication will be the only interaction that really matters.
This textbook presents the essential tools and core concepts of data science to public officials, policy analysts, and economists among others in order to further their application in the public sector. An expansion of the quantitative economics frameworks presented in policy and business schools, this book emphasizes the process of asking relevant questions to inform public policy. Its techniques and approaches emphasize data-driven practices, beginning with the basic programming paradigms that occupy the majority of an analyst’s time and advancing to the practical applications of statistical learning and machine learning. The text considers two divergent, competing perspectives to support its applications, incorporating techniques from both causal inference and prediction. Additionally, the book includes open-sourced data as well as live code, written in R and presented in notebook form, which readers can use and modify to practice working with data.
Robbie McEwen is one of the most successful road cyclists of the last 20 years, having achieved the rare distinction of winning over 100 professional races, including multiple stages in the prestigious Tour de France and Tour of Italy. At the Tour de France, he has taken the coveted Green Jersey three times.
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