Sampling and Estimation from Finite Populations - Yves Tille

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       Yves Tillé

      Université de Neuchâtel

      Switzerland

      Most of this book has been translated from French by Ilya Hekimi

      Original French title: Théorie des sondages : Échantillonnage et estimation en populations finies

      Copyright

      This edition first published 2020

      © 2020 John Wiley & Sons Ltd

      The right of Yves Tillé to be identified as the author of this work has been asserted in accordance with law.

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       Library of Congress Cataloging‐in‐Publication Data

      Names: Tillé, Yves, author. | Hekimi, Ilya, translator.

      Title: Sampling and estimation from finite populations / Yves Tillé ; most

      of this book has been translated from French by Ilya Hekimi.

      Other titles: Théorie des sondages. English

      Description: Hoboken, NJ : Wiley, [2020] | Series: Wiley series in

      probability and statistics applied. Probability and statistics section |

      Translation of: Théorie des sondages : échantillonnage et estimation

      en populations finies. | Includes bibliographical references and index.

      Identifiers: LCCN 2019048451 | ISBN 9780470682050 (hardback) | ISBN

      9781119071266 (adobe pdf) | ISBN 9781119071273 (epub)

      Subjects: LCSH: Sampling (Statistics) | Public opinion polls – Statistical

      methods. | Estimation theory.

      Classification: LCC QA276.6 .T62813 2020 | DDC 519.5/2 – dc23

      LC record available at https://lccn.loc.gov/2019048451

      Cover Design: Wiley

      Cover Image: © gremlin/Getty Images

      The first version of this book was published in 2001, the year I left the Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI) in Rennes (France) to teach at the University of Neuchâtel in Switzerland. This version came from several course materials of sampling theory that I had taught in Rennes. At the ENSAI, the collaboration with Jean‐Claude Deville was particularly stimulating.

      The editing of this new edition was laborious and was done in fits and starts. I thank all those who reviewed the drafts and provided me with their comments. Special thanks to Monique Graf for her meticulous re‐reading of some chapters.

      The almost 20 years I spent in Neuchâtel were dotted with multiple adventures. I am particularly grateful to Philippe Eichenberger and Jean‐Pierre Renfer, who successively headed the Statistical Methods Section of the Federal Statistical Office. Their trust and professionalism helped to establish a fruitful exchange between the Institute of Statistics of the University of Neuchâtel and the Swiss Federal Statistical Office.

      I am also very grateful to the PhD students that I have had the pleasure of mentoring so far. Each thesis is an adventure that teaches both supervisor and doctoral student. Thank you to Alina Matei, Lionel Quality, Desislava Nedyalkova, Erika Antal, Matti Langel, Toky Randrianasolo, Eric Graf, Caren Hasler, Matthieu Wilhelm, Mihaela Guinand‐Anastasiade, and Audrey‐Anne Vallée who trusted me and whom I had the pleasure to supervise for a few years.

       Yves Tillé

      Neuchâtel, 2018

      This book contains teaching material that I started to develop in 1994. All chapters have indeed served as a support for teaching, a course, training, a workshop or a seminar. By grouping this material, I hope to present a coherent and modern set of results on the sampling, estimation, and treatment of nonresponses, in other words, on all the statistical operations of a standard sample survey.

      In producing this book, my goal is not to provide a comprehensive overview of survey sampling theory, but rather to show that sampling theory is a living discipline, with a very broad scope. If, in several chapters demonstrations have been discarded, I have always been careful to refer the reader to bibliographical references. The abundance of very recent publications attests to the fertility of the 1990s in this area. All the developments presented in this book are based on the so‐called “design‐based” approach. In theory, there is another point of view based on population modeling. I intentionally left this approach aside, not out of disinterest, but to propose an approach that I deem consistent and ethically acceptable to the public statistician.

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