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Gone are the days of solely relying on intuition to make decisions. Today, number crunching affects your life in ways you might never imagine. Economist Ian Ayres shows how today's organizations are analyzing massive databases at lightning speed to provide greater insights into human behavior. From Web sites like Google and Amazon that know your tastes, to a physician's diagnosis or your child's education, to boardrooms and government agencies, this new breed of decisionmakers are calling the shots. And they are delivering staggeringly accurate results. How can a football coach evaluate a player without ever seeing him play? How can a formula outpredict wine experts in determining the best vintages? Super crunchers have the answers. In this brave new world of equation versus expertise, Ayres shows us the benefits and risks, who loses and who wins, and how super crunching can be used to help, not manipulate us.--From publisher description. Why would a casino try and stop you from losing? How can a mathematical formula find your future spouse? Would you know if a statistical analysis blackballed you from a job you wanted? Today, number crunching affects your life in ways you might never imagine. In this lively and groundbreaking new book, economist Ian Ayres shows how today's best and brightest organizations are analyzing massive databases at lightening speed to provide greater insights into human behavior. They are the Super Crunchers. From internet sites like Google and Amazon that know your tastes better than you do, to a physician's diagnosis and your child's education, to boardrooms and government agencies, this new breed of decision makers are calling the shots. And they are delivering staggeringly accurate results. How can a football coach evaluate a player without ever seeing him play? Want to know whether the price of an airline ticket will go up or down before you buy? How can a formula outpredict wine experts in determining the best vintages? Super crunchers have the answers. In this brave new world of equation versus expertise, Ayres shows us the benefits and risks, who loses and who wins, and how super crunching can be used to help, not manipulate us. Gone are the days of solely relying on intuition to make decisions. No businessperson, consumer, or student who wants to stay ahead of the curve should make another keystroke without reading Super Crunchers.

Statistics --- Regression analysis --- Sampling (Statistics) --- Standard deviations --- Statistique --- Analyse de régression --- Echantillonnage (Statistique) --- 311 --- besluitvorming --- kwantitatieve methoden --- regressie-analyse --- steekproeftechnieken --- wiskundige statistiek --- 519.2 --- Statistische methoden --- Probability. Mathematical statistics --- Regression analysis. --- Standard deviations. --- Statistics. --- Sampling (Statistics). --- 519.2 Probability. Mathematical statistics --- 311 Statistische methoden --- Analyse de régression --- #KVHB:Waarschijnlijkheidsrekening --- #KVHB:Getallenkrakers --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Deviations, Root-mean-square --- Deviations, Standard --- Root-mean-square deviations --- Analysis of variance --- Deviation (Mathematics) --- Random sampling --- Statistics of sampling --- Mathematical statistics --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- #KVHB:Statistiek --- statistique --- statistiek

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In the past decade, the study of networks has increased dramatically. Researchers from across the sciences—including biology and bioinformatics, computer science, economics, engineering, mathematics, physics, sociology, and statistics—are more and more involved with the collection and statistical analysis of network-indexed data. As a result, statistical methods and models are being developed in this area at a furious pace, with contributions coming from a wide spectrum of disciplines. This book provides an up-to-date treatment of the foundations common to the statistical analysis of network data across the disciplines. The material is organized according to a statistical taxonomy, although the presentation entails a conscious balance of concepts versus mathematics. In addition, the examples—including extended cases studies—are drawn widely from the literature. This book should be of substantial interest both to statisticians and to anyone else working in the area of ‘network science.’ The coverage of topics in this book is broad, but unfolds in a systematic manner, moving from descriptive (or exploratory) methods, to sampling, to modeling and inference. Specific topics include network mapping, characterization of network structure, network sampling, and the modeling, inference, and prediction of networks, network processes, and network flows. This book is the first such resource to present material on all of these core topics in one place. Eric Kolaczyk is a professor of statistics, and Director of the Program in Statistics, in the Department of Mathematics and Statistics at Boston University, where he also is an affiliated faculty member in the Center for Biodynamics, the Program in Bioinformatics, and the Division of Systems Engineering. His publications on network-based topics include work ranging from the detection of anomalous traffic patterns in computer networks to the prediction of biological function in networks of interacting proteins to the characterization of influence of groups of actors in social networks.

methodologieën --- informatica --- database management --- statistisch onderzoek --- sociale wetenschappen --- bio-informatica --- Mathematical statistics --- communicatietechnologie --- System analysis --- Analyse de systèmes --- Statistical methods. --- Méthodes statistiques. --- EPUB-LIV-FT LIVMATHE LIVSTATI SPRINGER-B --- Statistical methods --- Computer Communication Networks. --- Distribution (Probability theory. --- Mathematical statistics. --- Data mining. --- Bioinformatics. --- Probability Theory and Stochastic Processes. --- Statistical Theory and Methods. --- Complex Systems. --- Data Mining and Knowledge Discovery. --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Computational biology --- Systems biology --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Distribution functions --- Frequency distribution --- Characteristic functions --- Data processing --- 003.0727 --- informatique --- media --- statistiek --- Network analysis --- Network science --- Network theory --- Systems analysis --- System theory --- Mathematical optimization --- statistique --- Graphes, Théorie des. --- Graph theory --- Graphes aléatoires. --- Random graphs --- Computer networks --- Bioinformatics --- Réseaux d'ordinateurs --- Bioinformatique --- Computer communication systems. --- Probabilities. --- Statistics . --- Statistical physics. --- Dynamical systems. --- Probability --- Combinations --- Chance --- Least squares --- Risk --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Electronic data processing --- Network computers --- Dynamical systems --- Kinetics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics --- Distributed processing --- System analysis. --- System analysis - Statistical methods