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Titlebook: Modern Statistics; A Computer-Based App Ron S. Kenett,Shelemyahu Zacks,Peter Gedeck Textbook 2022 The Editor(s) (if applicable) and The Aut

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書目名稱Modern Statistics
副標(biāo)題A Computer-Based App
編輯Ron S. Kenett,Shelemyahu Zacks,Peter Gedeck
視頻videohttp://file.papertrans.cn/638/637414/637414.mp4
概述Demonstrates how to incorporate Python into the modern statistics curriculum.Includes over 40 case studies to facilitate experiential learning.An accompanying Python package is available for download,
叢書名稱Statistics for Industry, Technology, and Engineering
圖書封面Titlebook: Modern Statistics; A Computer-Based App Ron S. Kenett,Shelemyahu Zacks,Peter Gedeck Textbook 2022 The Editor(s) (if applicable) and The Aut
描述This innovative textbook presents material for a course on modern statistics that incorporates Python as a pedagogical and practical resource. Drawing on many years of teaching and conducting research in various applied and industrial settings, the authors have carefully tailored the text to provide an ideal balance of theory and practical applications.? Numerous examples and case studies are incorporated throughout, and comprehensive Python applications are illustrated in detail.? A custom Python package is available for download, allowing students to reproduce these examples and explore others..The first chapters of the text focus on analyzing variability, probability models, and distribution functions. Next, the authors introduce statistical inference and bootstrapping, and variability in several dimensions and regression models. The text then goes on to cover sampling for estimation of finite population quantities and time series analysis and prediction, concluding with two chapters on modern data analytic methods. Each chapter includes exercises, data sets, and applications to supplement learning..Modern Statistics: A Computer-Based Approach with Python.?is intended for a one-
出版日期Textbook 2022
關(guān)鍵詞Modern Statistics; Modern Statistics Python; data analysis; computer intensive statistical methods; boot
版次1
doihttps://doi.org/10.1007/978-3-031-07566-7
isbn_softcover978-3-031-07568-1
isbn_ebook978-3-031-07566-7Series ISSN 2662-5555 Series E-ISSN 2662-5563
issn_series 2662-5555
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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https://doi.org/10.1007/978-3-031-07566-7Modern Statistics; Modern Statistics Python; data analysis; computer intensive statistical methods; boot
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978-3-031-07568-1The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Modern Statistics978-3-031-07566-7Series ISSN 2662-5555 Series E-ISSN 2662-5563
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Conference proceedings 2015applications in experimental design theory and the theory of error-correcting codes, they have found unexpected and important applications in cryptography, quantum information theory, communications, and networking.
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