Thinking With Data
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Thinking With Data
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Author : Max Shron
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2014-01-20
Thinking With Data written by Max Shron and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-20 with Computers categories.
Many analysts are too concerned with tools and techniques for cleansing, modeling, and visualizing datasets and not concerned enough with asking the right questions. In this practical guide, data strategy consultant Max Shron shows you how to put the why before the how, through an often-overlooked set of analytical skills. Thinking with Data helps you learn techniques for turning data into knowledge you can use. You’ll learn a framework for defining your project, including the data you want to collect, and how you intend to approach, organize, and analyze the results. You’ll also learn patterns of reasoning that will help you unveil the real problem that needs to be solved. Learn a framework for scoping data projects Understand how to pin down the details of an idea, receive feedback, and begin prototyping Use the tools of arguments to ask good questions, build projects in stages, and communicate results Explore data-specific patterns of reasoning and learn how to build more useful arguments Delve into causal reasoning and learn how it permeates data work Put everything together, using extended examples to see the method of full problem thinking in action
Thinking With Data
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Author : Max Shron
language : en
Publisher:
Release Date : 2014
Thinking With Data written by Max Shron and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with SCIENCE categories.
Thinking Clearly With Data
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Author : Ethan Bueno de Mesquita
language : en
Publisher: Princeton University Press
Release Date : 2021-11-16
Thinking Clearly With Data written by Ethan Bueno de Mesquita and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-16 with Social Science categories.
An engaging introduction to data science that emphasizes critical thinking over statistical techniques An introduction to data science or statistics shouldn’t involve proving complex theorems or memorizing obscure terms and formulas, but that is exactly what most introductory quantitative textbooks emphasize. In contrast, Thinking Clearly with Data focuses, first and foremost, on critical thinking and conceptual understanding in order to teach students how to be better consumers and analysts of the kinds of quantitative information and arguments that they will encounter throughout their lives. Among much else, the book teaches how to assess whether an observed relationship in data reflects a genuine relationship in the world and, if so, whether it is causal; how to make the most informative comparisons for answering questions; what questions to ask others who are making arguments using quantitative evidence; which statistics are particularly informative or misleading; how quantitative evidence should and shouldn’t influence decision-making; and how to make better decisions by using moral values as well as data. Filled with real-world examples, the book shows how its thinking tools apply to problems in a wide variety of subjects, including elections, civil conflict, crime, terrorism, financial crises, health care, sports, music, and space travel. Above all else, Thinking Clearly with Data demonstrates why, despite the many benefits of our data-driven age, data can never be a substitute for thinking. An ideal textbook for introductory quantitative methods courses in data science, statistics, political science, economics, psychology, sociology, public policy, and other fields Introduces the basic toolkit of data analysis—including sampling, hypothesis testing, Bayesian inference, regression, experiments, instrumental variables, differences in differences, and regression discontinuity Uses real-world examples and data from a wide variety of subjects Includes practice questions and data exercises
Data Science For Business
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Author : Foster Provost
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-07-27
Data Science For Business written by Foster Provost and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-27 with Computers categories.
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates
Data Science Thinking
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Author : Longbing Cao
language : en
Publisher: Springer
Release Date : 2018-08-17
Data Science Thinking written by Longbing Cao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-17 with Computers categories.
This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective.
Thinking With Data
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Author : Marsha Lovett
language : en
Publisher: Psychology Press
Release Date : 2007
Thinking With Data written by Marsha Lovett and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Education categories.
First Published in 2007. Routledge is an imprint of Taylor & Francis, an informa company.
Storytelling With Data
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Author : Cole Nussbaumer Knaflic
language : en
Publisher: John Wiley & Sons
Release Date : 2015-10-09
Storytelling With Data written by Cole Nussbaumer Knaflic and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-09 with Mathematics categories.
Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!
Thinking With Data
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Author : Marsha C. Lovett
language : en
Publisher: Psychology Press
Release Date : 2012-08-21
Thinking With Data written by Marsha C. Lovett and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-21 with Psychology categories.
The chapters in Thinking With Data are based on presentations given at the 33rd Carnegie Symposium on Cognition. The Symposium was motivated by the confluence of three emerging trends: (1) the increasing need for people to think effectively with data at work, at school, and in everyday life, (2) the expanding technologies available to support people as they think with data, and (3) the growing scientific interest in understanding how people think with data. What is thinking with data? It is the set of cognitive processes used to identify, integrate, and communicate the information present in complex numerical, categorical, and graphical data. This book offers a multidisciplinary presentation of recent research on the topic. Contributors represent a variety of disciplines: cognitive and developmental psychology; math, science, and statistics education; and decision science. The methods applied in various chapters similarly reflect a scientific diversity, including qualitative and quantitative analysis, experimentation and classroom observation, computational modeling, and neuroimaging. Throughout the book, research results are presented in a way that connects with both learning theory and instructional application. The book is organized in three sections: Part I focuses on the concepts of uncertainty and variation and on how people understand these ideas in a variety of contexts. Part II focuses on how people work with data to understand its structure and draw conclusions from data either in terms of formal statistical analyses or informal assessments of evidence. Part III focuses on how people learn from data and how they use data to make decisions in daily and professional life.
Thinking With Theory In Qualitative Research
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Author : Alecia Youngblood Jackson
language : en
Publisher: Routledge
Release Date : 2011-12-02
Thinking With Theory In Qualitative Research written by Alecia Youngblood Jackson and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-02 with Education categories.
Winner of the 2013 American Educational Studies Association's Critics Choice Award! Thinking With Theory In Qualitative Research shows how to use various philosophical concepts in practices of inquiry; effectively opening up the process of data analysis in qualitative research. It uses a common data set and utilizes various theoretical perspectives through which to view the data. It challenges qualitative researchers to use theory to accomplish a rigorous, analytic reading of qualitative data. "Plugging in" the theory and the data produces a variety of readings applying various theorists and their concepts, including: Derrida - Deconstruction Spivak – Postcolonial Marginality Foucault - Power/Knowledge Butler - Performativity Deleuze – Desire Barad – Material Intra-activity Thinking With Theory In Qualitative Research pushes against traditional qualitative data analysis such as mechanistic coding, reducing data to themes, and writing up transparent narratives. These do little to critique the complexities of social life; such simplistic approaches preclude dense and multi-layered treatment of data. It shows that "thinking with theory" pushes research and data and theory to its exhaustion in order to produce knowledge differently. By refusing a closed system for fixed meaning, a new analytic is engaged to keep meaning on the move. The result is an extension of thought beyond an easy sense. Special features of the book include schematic cues to help guide the reader through what might be new theoretical terrain, interludes that explain the possibilities of thinking with a particular concept and theorist and detailed chapters that plug the same data set into a specific concept. This vital tool will help researchers understand and fully utilize their powers of data analysis and will prove invaluable to both students and experienced researchers across all of the social sciences.
Modes Of Thinking For Qualitative Data Analysis
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Author : Melissa Freeman
language : en
Publisher: Routledge
Release Date : 2016-09-20
Modes Of Thinking For Qualitative Data Analysis written by Melissa Freeman and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-20 with Education categories.
Modes of Thinking for Qualitative Data Analysis argues for engagement with the conceptual underpinnings of five prominent analytical strategies used by qualitative researchers: Categorical Thinking, Narrative Thinking, Dialectical Thinking, Poetical Thinking, and Diagrammatical Thinking. By presenting such disparate modes of research in the space of a single text, Freeman not only draws attention to the distinct methodological and theoretical contributions of each, she also establishes a platform for choosing among particular research strategies by virtue of their strengths and limitations. Experienced qualitative researchers, novices, and graduate students from many disciplines will gain new insight from the theory-practice relationship of analysis advanced in this text.