Published by Springer Nature (edition 1st ed. 2016), 2017
ISBN 10: 3319461605 ISBN 13: 9783319461601
Language: English
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First Edition
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Published by Springer International Publishing AG, CH, 2024
ISBN 10: 3031120256 ISBN 13: 9783031120251
Language: English
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Paperback. Condition: New. Second Edition 2022. 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.
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Published by Springer International Publishing AG, CH, 2024
ISBN 10: 3031120256 ISBN 13: 9783031120251
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
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Add to basketPaperback. Condition: New. Second Edition 2022. 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.