« Cet ouvrage de référence expose les fondements mathématiques et méthodologiques des enquêtes par sondage et fournit un cadre théorique pour mesurer leurs performances. Il présente des développements sur les méthodes d'échantillonnage, sur les techniques d'estimation et de redressement et des éléments permettant de calculer la précision des résultats obtenus. »--Page 4 de la couverture.
Whenweagreedtoshareallofourpreparationofexercisesinsamplingtheory to create a book, we were not aware of the scope of the work. It was indeed necessary to compose the information, type out the compilations, standardise the notations and correct the drafts. It is fortunate that we have not yet measured the importance of this project, for this work probably would never have been attempted! In making available this collection of exercises, we hope to promote the teaching of sampling theory for which we wanted to emphasise its diversity. The exercises are at times purely theoretical while others are originally from real problems, enabling us to approach the sensitive matter of passing from theory to practice that so enriches survey statistics. The exercises that we present were used as educational material at the École Nationale de la Statistique et de l’Analyse de l’Information (ENSAI), where we had successively taught sampling theory. We are not the authors of all the exercises. In fact, some of them are due to Jean-Claude Deville and Laurent Wilms. We thank them for allowing us to reproduce their exercises. It is also possible that certain exercises had been initially conceived by an author that we have not identi?ed. Beyondthe contribution of our colleagues, and in all cases, we do not consider ourselves to be the lone authors of these exercises:they actually form part of a common heritagefrom ENSAI that has been enriched and improved due to questions from students and the work of all the demonstrators of the sampling course at ENSAI.
This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the “curse of dimensionality”, their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the field and discusses the state of the art concerning sampling techniques for supervised and unsupervised task. Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks; Describe implementation and evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality; Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. "This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge." M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas "In science the difficulty is not to have ideas, but it is to make them work" From Carlo Rovelli
A much-needed reference on survey sampling and its applications that presents the latest advances in the field Seeking to show that sampling theory is a living discipline with a very broad scope, this book examines the modern development of the theory of survey sampling and the foundations of survey sampling. It offers readers a critical approach to the subject and discusses putting theory into practice. It also explores the treatment of non-sampling errors featuring a range of topics from the problems of coverage to the treatment of non-response. In addition, the book includes real examples, applications, and a large set of exercises with solutions. Sampling and Estimation from Finite Populations begins with a look at the history of survey sampling. It then offers chapters on: population, sample, and estimation; simple and systematic designs; stratification; sampling with unequal probabilities; balanced sampling; cluster and two-stage sampling; and other topics on sampling, such as spatial sampling, coordination in repeated surveys, and multiple survey frames. The book also includes sections on: post-stratification and calibration on marginal totals; calibration estimation; estimation of complex parameters; variance estimation by linearization; and much more. Provides an up-to-date review of the theory of sampling Discusses the foundation of inference in survey sampling, in particular, the model-based and design-based frameworks Reviews the problems of application of the theory into practice Also deals with the treatment of non sampling errors Sampling and Estimation from Finite Populations is an excellent book for methodologists and researchers in survey agencies and advanced undergraduate and graduate students in social science, statistics, and survey courses.
Survey Methodology is becoming a more structured field of research, deserving of more and more academic attention. The SAGE Handbook of Survey Methodology explores both the increasingly scientific endeavour of surveys and their growing complexity, as different data collection modes and information sources are combined. The handbook takes a global approach, with a team of international experts looking at local and national specificities, as well as problems of cross-national, comparative survey research. The chapters are organized into seven major sections, each of which represents a stage in the survey life-cycle: Surveys and Societies Planning a Survey Measurement Sampling Data Collection Preparing Data for Use Assessing and Improving Data Quality The SAGE Handbook of Survey Methodology is a landmark and essential tool for any scholar within the social sciences.
L’électrographie de fond de mer (EFM) regroupe les méthodes électromagnétiques d’exploration du sous-sol marin et plus spécifiquement celles dédiées à la prospection des hydrocarbures en mer. Apparues commercialement en 2000, ces techniques, avec plus de 500 opérations industrielles, présentent après 10 ans de succès commerciaux un taux record de découverte de près de 90 %, et semblent aujourd’hui bouleverser la donne en matière de recherche pétrolière offshore. En proposant un indice de présence d’hydrocarbures sérieux, l’EFM couplée à la sismique réflexion est probablement la première méthode fiable de détection directe des hydrocarbures. Complétant les concepts structuralistes de la prospection indirecte en vigueur depuis les années 1920, l’EFM modifie aujourd’hui radicalement l’approche et les philosophies d’exploration, en particulier celles incluant en aval les activités de forages et de diagraphies de fond de trou. S’appuyant sur les lois de l’électromagnétisme (équations de Maxwell), Électrographies de fond de mer décrit et analyse en détail les principes physiques, les méthodes, les techniques et les technologies mis en œuvre ou en voie de l’être. De plus, une note historique montrant l’évolution des idées, des concepts et des matériels depuis les années 1930, dates des premières tentatives, complète chaque chapitre. Synthèse unique, cet ouvrage abondamment illustré constitue un véritable outil de réflexion sur l’utilisation en prospection de l’énergie électromagnétique en milieu conducteur (eau de mer) fixant ainsi les limites théoriques et pratiques de ces investigations pour les développements à venir. Destiné aux géophysiciens et géologues du pétrole, il sera également utile aux physiciens du globe, aux ingénieurs réservoir, aux diagraphistes, aux log analysts, ainsi qu’à tous les étudiants en géosciences.
