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Titlebook: Statistics for Health Data Science; An Organic Approach Ruth Etzioni,Micha Mandel,Roman Gulati Textbook 2020 The Author(s), under exclusive

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書目名稱Statistics for Health Data Science
副標(biāo)題An Organic Approach
編輯Ruth Etzioni,Micha Mandel,Roman Gulati
視頻videohttp://file.papertrans.cn/877/876736/876736.mp4
概述Highly interdisciplinary - drawing from statistics, health services, economics, and informatics.Goes beyond the formulas, explaining why different methods work, how to choose from among them, and how
叢書名稱Springer Texts in Statistics
圖書封面Titlebook: Statistics for Health Data Science; An Organic Approach Ruth Etzioni,Micha Mandel,Roman Gulati Textbook 2020 The Author(s), under exclusive
描述.Students and researchers in the health sciences are faced with greater opportunity and challenge than ever before. The opportunity stems from the explosion in publicly available data that simultaneously informs and inspires new avenues of investigation. The challenge is that the analytic tools required go far beyond the standard methods and models of basic statistics. This textbook aims to equip health care researchers with the most important elements of a modern health analytics toolkit, drawing from the fields of statistics, health econometrics, and data science..This textbook is designed to overcome students’ anxiety about data and statistics?and to help them to become confident users of appropriate analytic methods for health care research studies.?Methods are presented organically, with new material building naturally on what has come before. Each technique is motivated by a topical research question, explained in non-technical terms, and accompanied by engagingexplanations and examples. In this way, the authors cultivate a deep (“organic”) understanding of a range of analytic techniques, their assumptions and data requirements, and their advantages and limitations. They illu
出版日期Textbook 2020
關(guān)鍵詞Analytic Methods; Biostatistics; Data Science; Epidemiology; Health Care Databases; Health Data Analytics
版次1
doihttps://doi.org/10.1007/978-3-030-59889-1
isbn_softcover978-3-030-59891-4
isbn_ebook978-3-030-59889-1Series ISSN 1431-875X Series E-ISSN 2197-4136
issn_series 1431-875X
copyrightThe Author(s), under exclusive licence to Springer Nature Switzerland AG 2020
The information of publication is updating

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Statistics for Health Data Science978-3-030-59889-1Series ISSN 1431-875X Series E-ISSN 2197-4136
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1431-875X ferent methods work, how to choose from among them, and how .Students and researchers in the health sciences are faced with greater opportunity and challenge than ever before. The opportunity stems from the explosion in publicly available data that simultaneously informs and inspires new avenues of
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Statistics and Health Data,ealth students and practitioners as they navigate this changing landscape to develop competence as health data analysts. In this chapter, we define the concept of organic statistics, which will form a foundation for the methods presented in this and subsequent chapters. We differentiate between hypo
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