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Special order direct from the distributor. N° de réf. du vendeur ING9783031120251
Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference.
The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.
À propos de l?auteur:
Dr. Christian Heumann is a Professor at the Department of Statistics, LMU Munich, Germany, where he teaches students in both the Bachelor's and Master's programs. His research interests include statistical modeling, computational statistics and methods for missing data, also in connection with causal inference. Recently, he has begun exploring statistical methods in natural language processing.
Dr. Michael Schomaker is a Researcher and Heisenberg Fellow at the Department of Statistics, LMU Munich, Germany. He is an honorary Senior Lecturer at the University of Cape Town, South Africa and previously worked as an Associate Professor at UMIT - University for Health Sciences, Medical Informatics and Technology, Austria. For many years he has taught both undergraduate and post-graduate students from various disciplines, including the business and medical sciences, and has written contributions for various introductory textbooks. His research focuses on causal inference, missing data, model averaging, and HIV and public health.
Dr. Shalabh is a Professor at the Indian Institute of Technology Kanpur, India. As a post-doctoral researcher he worked at the University of Pittsburgh, USA and LMU Munich, Germany. He has over twenty-five years of experience in teaching and research. His main research areas are linear models, regression analysis, econometrics, error-measurement models, missing data models and sampling theory.
Titre : Introduction to Statistics and Data Analysis...
Éditeur : Springer
Date d'édition : 2024
Reliure : paperback
Etat : New
Edition : Second Edition 2022.
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader thr. N° de réf. du vendeur 1341574260
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Taschenbuch. Etat : Neu. Introduction to Statistics and Data Analysis | With Exercises, Solutions and Applications in R | Christian Heumann (u. a.) | Taschenbuch | xvii | Englisch | 2024 | Springer | EAN 9783031120251 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 128284817
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Taschenbuch. Etat : Neu. Neuware -Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference.The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 604 pp. Englisch. N° de réf. du vendeur 9783031120251
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference.The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications. N° de réf. du vendeur 9783031120251
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference.The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications. 604 pp. Englisch. N° de réf. du vendeur 9783031120251
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