Full Description
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.
Contents
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
