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

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

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.

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

Radically reimagine our ways of being, learning, and doing Education can be transformed if we eradicate our fixation on big data like standardized test scores as the supreme measure of equity and learning. Instead of the focus being on "fixing" and "filling" academic gaps, we must envision and rebuild the system from the student up—with classrooms, schools and systems built around students’ brilliance, cultural wealth, and intellectual potential. Street data reminds us that what is measurable is not the same as what is valuable and that data can be humanizing, liberatory and healing. By breaking down street data fundamentals: what it is, how to gather it, and how it can complement other forms of data to guide a school or district’s equity journey, Safir and Dugan offer an actionable framework for school transformation. Written for educators and policymakers, this book · Offers fresh ideas and innovative tools to apply immediately · Provides an asset-based model to help educators look for what’s right in our students and communities instead of seeking what’s wrong · Explores a different application of data, from its capacity to help us diagnose root causes of inequity, to its potential to transform learning, and its power to reshape adult culture Now is the time to take an antiracist stance, interrogate our assumptions about knowledge, measurement, and what really matters when it comes to educating young people.

First Published in 2007. Routledge is an imprint of Taylor & Francis, an informa company.

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