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Titlebook: Modern Survey Analysis; Using Python for Dee Walter R. Paczkowski Book 2022 The Editor(s) (if applicable) and The Author(s), under exclusiv

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發(fā)表于 2025-3-21 17:01:28 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Modern Survey Analysis
副標(biāo)題Using Python for Dee
編輯Walter R. Paczkowski
視頻videohttp://file.papertrans.cn/638/637419/637419.mp4
概述Discusses data visualization for survey data, so that readers can conduct more sophisticated analyses.Uses Python to illustrate concepts.Includes a Jupyter notebook with data and Python code, so that
圖書(shū)封面Titlebook: Modern Survey Analysis; Using Python for Dee Walter R. Paczkowski Book 2022 The Editor(s) (if applicable) and The Author(s), under exclusiv
描述.This book develops survey data analysis tools in Python, to create and analyze cross-tab tables and data visuals, weight data, perform hypothesis tests, and handle special survey questions such as Check-all-that-Apply. In addition, the basics of Bayesian data analysis and its Python implementation are presented. Since surveys are widely used as the primary method to collect data, and ultimately information, on attitudes, interests, and opinions of customers and constituents, these tools are vital for private or public sector policy decisions..As a compact volume, this book uses case studies to illustrate methods of analysis essential for those who work with survey data in either sector. It focuses on two overarching objectives:.Demonstrate how to extract actionable, insightful,and useful information from survey data; and.Introduce Python and Pandas for analyzing surveydata.. .
出版日期Book 2022
關(guān)鍵詞Python; consulting; market research; surveys; data analytics; regression models; Pandas; survey data visual
版次1
doihttps://doi.org/10.1007/978-3-030-76267-4
isbn_softcover978-3-030-76269-8
isbn_ebook978-3-030-76267-4
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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978-3-030-76269-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Walter R. PaczkowskiDiscusses data visualization for survey data, so that readers can conduct more sophisticated analyses.Uses Python to illustrate concepts.Includes a Jupyter notebook with data and Python code, so that
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Book 2022o illustrate methods of analysis essential for those who work with survey data in either sector. It focuses on two overarching objectives:.Demonstrate how to extract actionable, insightful,and useful information from survey data; and.Introduce Python and Pandas for analyzing surveydata.. .
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ludes a Jupyter notebook with data and Python code, so that .This book develops survey data analysis tools in Python, to create and analyze cross-tab tables and data visuals, weight data, perform hypothesis tests, and handle special survey questions such as Check-all-that-Apply. In addition, the bas
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Basic notions,quipped with truncated addition . = min(1, .) and negation 1 - .. We show that every MV-algebra contains a natural lattice-order. The chapter culminates with Chang’s Subdirect Representation Theorem, stating that if an equation holds in all totally ordered MV-algebras, then the equation holds in all
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