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Thinking Clearly with Data

Thinking Clearly with Data
Author: Ethan Bueno de Mesquita
Publisher: Princeton University Press
Total Pages: 400
Release: 2021-11-16
Genre: Social Science
ISBN: 0691215014

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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


Thinking with Data

Thinking with Data
Author: Max Shron
Publisher: "O'Reilly Media, Inc."
Total Pages: 105
Release: 2014-01-20
Genre: Computers
ISBN: 1491949775

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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


Big Data

Big Data
Author: Viktor Mayer-Schönberger
Publisher: Houghton Mifflin Harcourt
Total Pages: 257
Release: 2013
Genre: Business & Economics
ISBN: 0544002695

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A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large.


Thinking Clearly

Thinking Clearly
Author: Jill LeBlanc
Publisher: W W Norton & Company Incorporated
Total Pages: 314
Release: 1998
Genre: Philosophy
ISBN: 9780393972184

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In tune with the needs of students, Thinking Clearly focuses squarely on core issues of critical reasoning.


The Art of Thinking Clearly

The Art of Thinking Clearly
Author: Rolf Dobelli
Publisher: Harper Collins
Total Pages: 269
Release: 2014-05-06
Genre: Psychology
ISBN: 0062359800

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A world-class thinker counts the 100 ways in which humans behave irrationally, showing us what we can do to recognize and minimize these “thinking errors” to make better decisions and have a better life Despite the best of intentions, humans are notoriously bad—that is, irrational—when it comes to making decisions and assessing risks and tradeoffs. Psychologists and neuroscientists refer to these distinctly human foibles, biases, and thinking traps as “cognitive errors.” Cognitive errors are systematic deviances from rationality, from optimized, logical, rational thinking and behavior. We make these errors all the time, in all sorts of situations, for problems big and small: whether to choose the apple or the cupcake; whether to keep retirement funds in the stock market when the Dow tanks, or whether to take the advice of a friend over a stranger. The “behavioral turn” in neuroscience and economics in the past twenty years has increased our understanding of how we think and how we make decisions. It shows how systematic errors mar our thinking and under which conditions our thought processes work best and worst. Evolutionary psychology delivers convincing theories about why our thinking is, in fact, marred. The neurosciences can pinpoint with increasing precision what exactly happens when we think clearly and when we don’t. Drawing on this wide body of research, The Art of Thinking Clearly is an entertaining presentation of these known systematic thinking errors--offering guidance and insight into everything why you shouldn’t accept a free drink to why you SHOULD walk out of a movie you don’t like it to why it’s so hard to predict the future to why shouldn’t watch the news. The book is organized into 100 short chapters, each covering a single cognitive error, bias, or heuristic. Examples of these concepts include: Reciprocity, Confirmation Bias, The It-Gets-Better-Before-It-Gets-Worse Trap, and the Man-With-A-Hammer Tendency. In engaging prose and with real-world examples and anecdotes, The Art of Thinking Clearly helps solve the puzzle of human reasoning.


All Data Are Local

All Data Are Local
Author: Yanni Alexander Loukissas
Publisher: MIT Press
Total Pages: 267
Release: 2019-04-30
Genre: Computers
ISBN: 0262039664

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How to analyze data settings rather than data sets, acknowledging the meaning-making power of the local. In our data-driven society, it is too easy to assume the transparency of data. Instead, Yanni Loukissas argues in All Data Are Local, we should approach data sets with an awareness that data are created by humans and their dutiful machines, at a time, in a place, with the instruments at hand, for audiences that are conditioned to receive them. The term data set implies something discrete, complete, and portable, but it is none of those things. Examining a series of data sources important for understanding the state of public life in the United States—Harvard's Arnold Arboretum, the Digital Public Library of America, UCLA's Television News Archive, and the real estate marketplace Zillow—Loukissas shows us how to analyze data settings rather than data sets. Loukissas sets out six principles: all data are local; data have complex attachments to place; data are collected from heterogeneous sources; data and algorithms are inextricably entangled; interfaces recontextualize data; and data are indexes to local knowledge. He then provides a set of practical guidelines to follow. To make his argument, Loukissas employs a combination of qualitative research on data cultures and exploratory data visualizations. Rebutting the “myth of digital universalism,” Loukissas reminds us of the meaning-making power of the local.


Data Science for Business

Data Science for Business
Author: Foster Provost
Publisher: "O'Reilly Media, Inc."
Total Pages: 414
Release: 2013-07-27
Genre: Computers
ISBN: 144937428X

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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 Feminism

Data Feminism
Author: Catherine D'Ignazio
Publisher: MIT Press
Total Pages: 328
Release: 2023-10-03
Genre: Social Science
ISBN: 026254718X

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A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.


Analyzing Quantitative Data

Analyzing Quantitative Data
Author: Norman Blaikie
Publisher: SAGE
Total Pages: 380
Release: 2003-03-06
Genre: Social Science
ISBN: 9780761967590

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For social researchers who need to know what procedures to use under what circumstances in practical research projects, this book does not require an indepth understanding of statistical theory.


Introduction to Educational Research

Introduction to Educational Research
Author: W. Newton Suter
Publisher: SAGE
Total Pages: 529
Release: 2012
Genre: Education
ISBN: 1412995736

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"Introduction to Educational Research: A Critical Thinking Approach 2e is an engaging and informative core text that enables students to think clearly and critically about the scientific process of research. In acheiving its goal to make research accessible to all educators and equip them with the skills to understand and evaluate published research, the text examines how educational research is conducted across the major traditions of quantitative, qualitative, mixed methods, and action research. The text is oriented toward consumers of educational research and uses a thinking-skills approach to its coverage of major ideas"--