Super Crunchers - How Anything Can be Predicted

Informationen zum Autor Ian Ayres is a professor at Yale both in the Law School and in the School of Management, as well as a lawyer and author. He is a regular commentator on National Public Radio in America and a columnist for Forbes magazine. A contributor to the New York Times and editor of the Journal of Law, Economics and Organization , he has written several books. Klappentext Companies used to rely on human experts and their years of experience to guide them. Now, cutting-edge organizations are mining the data and crunching numbers instead, to come up with more accurate, less biased predictions. As FREAKONOMICS detailed, statistical analysis can reveal the secret levers of causation. But economist Ian Ayres argues that that's only part of the story: super crunching is revolutionizing the way we all make decisions. Beginning with examples of the mathematician who out-predicted wine buffs in determining the best vintages, and the sports scouts who now use statistics rather than intuition to pick winners, SUPER CRUNCHERS exposes the world of data-miners, introducing the people and the techniques. It illuminates the hidden patterns all around us. No businessperson, academic, student, or consumer should make another move without getting to grips with thinking-by-numbers - the new way to be smart, savvy and statistically superior. Zusammenfassung Super Crunchers are the pioneers who 'think by numbers' to find patterns in human behaviour and predict the future - with staggeringly accurate results

Détails du produit

• Auteurs: Ian Ayres, Ayres Ian
• Edition: John Murray
• Langues: Anglais
• Format d'édition: Poche format B
• Sortie: 01.05.2008
• EAN: 9780719564659
• ISBN: 978-0-7195-6465-9
• Pages: 260
• Dimensions: 130 mm x 196 mm x 18 mm
• Catégories: Sciences naturelles, médecine, informatique, technique > Informatique, ordinateurs > Général, dictionnaires; Sciences sociales, droit, économie > Economie > Gestion; Entscheidung, Statistik, Datenanalyse, BUSINESS & ECONOMICS / Decision-Making & Problem Solving, Data science and analysis