Includes index.

"This is an intro-level text that teaches how to think clearly and conceptually about quantitative information, emphasizing ideas over technicality and assuming no prior exposure to data analysis, statistics, or quantitative methods. The books four parts present the foundation for quantiative reasoning: correlation and causation; statistical relationships; causal phenomena; and incorporating quantitative information into decision making. Within these parts it covers the array of tools used by social scientists, including regression, inference, experiments, research design, and more, all by explaining the rationale and logic behind such tools rather than focusing only on the technical calculations used for each. New concepts are presented simply, with the help of copious examples, and the books leans towards graphic rather than mathematical representation of data, with any technical material included in appendices"-- $c Provided by publisher.

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.