Truth Addict

Foreword by Charles Wheelan, author of New York Times bestseller Naked Statistics: Stripping the Dread from the Data What makes some evidence strong, some evidence weak, and some evidence total nonsense? Truth Addict is your guide to answers. Individuals, policymakers, and businesses across the globe want to make decisions based on evidence. But not all evidence is created equal. Truth Addict is the layperson's guide to data, truth, and the gap between them. Whether it's collected through laboratory experiments or public surveys, market research or archival records, data has a story to tell us-but only if we can read it. Drawing on engaging examples, John V. Kane details the logic of gathering and analyzing data as a means of getting us closer to the truth, even if the truth hurts. Developing research questions. Defining variables. Choosing metrics. Testing hypotheses. Quantifying relationships. Ruling out chance. Considering alternative explanations. Knowing not just that "correlation does not equal causation," but also how to tell the difference. These are key steps along Kane's "Road to Evidence," a journey that begins with curiosity and ends at objective knowledge. You don't have to be a math whiz to study our social world-Truth Addict provides every reader tools to uncover the reality within the numbers.

John V. Kane is Associate Professor at the Center for Global Affairs at New York University, where he teaches courses on research methods, applied statistics, and public opinion. He has written for top peer-reviewed journals, as well as for The New York Times, National Public Radio, and elsewhere.

Contents List of Illustrations Acknowledgments Foreword by Charles Wheelan Introduction Level 1: A Problem of Motivation Chapter 1: What Are We Talking About? Chapter 2: Motivated to Believe (What We Want to Be True) Chapter 3: Aiming for Accuracy (Even When the Truth Hurts) Level 2: It All Begins with a Question Chapter 4: Asking the Right Questions Chapter 5: Research Questions Have Two Variables We Care About Chapter 6: First Formulate, Then Fixate Level 3: Learning the Lingo, Loving the Logic Chapter 7: Homing In On a Hypothesis Chapter 8: The Mechanism Matters Chapter 9: Design Intelligently Chapter 10: Out of the Sky and into the Spreadsheet Chapter 11: Comparison, the Giver of Knowledge Level 4: Finding Meaning in the Findings Chapter 12: The Numbers We Really Care About Chapter 13: Go Figures Chapter 14: Wrestling with Randomness Chapter 15: Sizing Up the Results Level 5: Data, Data Everywhere, Now Let Us Stop to Think Chapter 16: Separating the Three C's-Coincidence, Correlation, and Causation Chapter 17: Reading Results in Reverse, and the Evil Powers of Hidden Confounders Chapter 18: What Should We Conclude? (Flaws, Limitations, and Implications) Chapter 19: The Slow, Careful Crawl Toward Truth Conclusion: The Truth Is Out There (Now Go and Find It) Notes References Index