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Hydrologie --- Cours d'eau --- Donnees numeriques --- Hydrologie --- Regime, debit --- Cours d'eau --- Cours d'eau --- Hydrologie --- Cours d'eau --- Donnees numeriques --- Hydrologie --- Regime, debit --- Cours d'eau --- Donnees numeriques --- Cours d'eau --- Regime, debit
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Santé mentale --- Santé mentale --- Santé mentale --- Statistiques et données numériques. --- Statistiques. --- Planification.
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Rhin (vallee) --- Hydrologie --- Cours d'eau --- Europe --- Europe. --- Rhin (vallee) --- Hydrologie --- Cours d'eau --- Donnees numeriques
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Aide alimentaire --- Food aid --- Pays en développement --- Developing countries --- FAO --- Méthode statistique --- Statistical methods --- world --- Donnees numeriques
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'Theater as data' explores the use of computational methods and digital data in theater research, the implications of these new approaches, and the roles that statistics and visualizations play. Miguel Escobar Varela suggests that both ways of using data have a place in theater research : data-driven methods are closer to the interpretive traditions of the humanities. The book surveys four major areas within theater scholarship : texts (not only playscripts, but also theater reviews and program booklets); relationships (both the links between fictional characters and the collaborative networks of artists and producers); motion (the movement of performers and objects on stage); and locations (the coordinates of performance events, venues, and touring circuits). The book examines important computational theater research in classical French drama, collaboration networks in Australian theater, contemporary Portuguese choreography, and global productions of Ibsen, and includes descriptions of the author's own computational analysis of theater practices in Singapore and Indonesia. Finally, the book considers the future of computational theater research, underlining the importance of open data and digital sustainability practices, and encouraging readers to consider the benefits of learning to code. A web companion to the book offers illustrative data, programming tutorials, and videos.
Theater - Research - Data processing --- Theater - Research - Methodology --- Computers in the theater --- Theater --- Recherche théâtrale --- Statistiques --- Codage --- Méthodes --- Informatique --- Données numériques --- Base de données
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Géologie --- Amerique du nord --- Hydrologie --- Etats-unis --- Cours d'eau --- Amerique du nord --- Hydrologie --- Etats-unis --- Cours d'eau --- Donnees numeriques
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Hydrologie --- Hydrologie --- Hydrologie --- Cours d'eau --- Hydrologie regionale --- Cours d'eau --- Hydrologie --- Hydrologie --- Hydrologie --- Cours d'eau --- Pollution --- Hydrologie regionale --- Cours d'eau --- Donnees numeriques
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Ce mémoire entend approcher l'économie des plateformes numériques à travers le prisme des valuations studies. Seront alors observés les pouvoirs de valorisation que possèdent les plateformes numériques en établissant - ou pas - des dispositifs évaluatifs.
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On assiste actuellement à la multiplication des données numériques provenant de diverses sources : les administrations mettent en ligne leurs données de fonctionnement dans le cadre de démarches open data, les entreprises ouvrent certaines de leurs données non stratégiques, le monde scientifique utilise des données hétérogènes et de grande taille, et les internautes produisent des données à travers leurs activités quotidiennes sur le web. Loin d’être simplement mises en ligne, ces données sont « mises à disposition » des utilisateurs en vue de créer de nouveaux services et d’améliorer la connaissance des pratiques sociales. Comme le montre les discours d’accompagnement produits par les différents acteurs, les espoirs placés dans les données numériques sont nombreux et les transformations annoncées sont bien souvent présentées comme inéluctable et par défaut source de progrès. Loin de considérer cet « impératif d’ouverture » comme immuable, l’ambition du présent ouvrage est d’interroger de manière critique les multiples processus sociotechniques au sein desquels les données s’insèrent, de leur production à leur usage. Cette démarche propose d’ouvrir des pistes de réflexions pour mieux appréhender les évolutions de notre environnement numérique.
Information Science & Library Science --- Social Sciences, Interdisciplinary --- big data --- données numériques --- empowerment --- épistémologie des SHS --- gouvernement des données --- infrastructures informationnelles --- open data --- partage de données --- data sharing --- information infrastructure --- empowement --- epistemology --- political accountability --- science --- social science
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This book provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but these innovations are insufficiently applied in medical research. Old-fashioned, data hungry methods are often used in data sets of limited size, validation of predictions is not done or done simplistically, and updating of previously developed models is not considered. A sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice. Clinical prediction models presents a practical checklist with seven steps that need to be considered for development of a valid prediction model. These include preliminary considerations such as dealing with missing values; coding of predictors; selection of main effects and interactions for a multivariable model; estimation of model parameters with shrinkage methods and incorporation of external data; evaluation of performance and usefulness; internal validation; and presentation formats. The steps are illustrated with many small case-studies and R code, with data sets made available in the public domain. The book further focuses on generalizability of prediction models, including patterns of invalidity that may be encountered in new settings, approaches to updating of a model, and comparisons of centers after case-mix adjustment by a prediction model. The text is primarily intended for clinical epidemiologists and biostatisticians. It can be used as a textbook for a graduate course on predictive modeling in diagnosis and prognosis. It is beneficial if readers are familiar with common statistical models in medicine: linear regression, logistic regression, and Cox regression. The book is practical in nature. But it provides a philosophical perspective on data analysis in medicine that goes beyond predictive modeling. In this era of evidence-based medicine, randomized clinical trials are the basis for assessment of treatment efficacy. Prediction models are key to individualizing diagnostic and treatment decision making. Ewout Steyerberg (1967) is Professor of Medical Decision Making, in particular prognostic modeling, at Erasmus MC-University Medical Center Rotterdam, the Netherlands. His work on prediction models was stimulated by various research grants including a fellowship from the Royal Netherlands Academy of Arts and Sciences. He has published over 250 peer-reviewed articles in collaboration with many clinical researchers, both in methodological and medical journals.
Biomathematics. Biometry. Biostatistics --- medische statistiek --- biostatistiek --- Models, Statistical. --- Prognosis. --- Regression Analysis. --- Medical statistics. --- Medicine --- Evidence-based medicine --- Clinical trials --- Regression analysis. --- Statistique médicale --- Médecine --- Etudes cliniques --- Analyse de régression --- Research --- Statistical methods. --- Recherche --- Méthodes statistiques --- EPUB-LIV-FT LIVMATHE LIVSTATI SPRINGER-B --- Medical statistics --- Regression Analysis --- Statistical methods --- Analyse de régression. --- Études cliniques --- Médecine fondée sur la preuve --- Médecine --- Statistiques médicales. --- Statistiques. --- Statistiques et données numériques. --- Medicine - Research - Statistical methods --- Evidence-based medicine - Statistical methods --- Clinical trials - Statistical methods
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