Why Averages Lie: When Summary Statistics Mislead
The same data tells opposite stories depending on which summary statistic you choose to report
How to Spot Misleading Percentages in Headlines
Three questions that reveal whether a percentage is informing you or misleading you
The Bayesian Revolution: A Different Way to Think About Probability
Why what you already know should shape how you interpret new evidence—and the math that makes this precise
The Measurement Problem: Why Quantifying Human Behavior Is Hard
Why measuring human minds requires different tools and expectations than measuring physical objects
Why Weather Forecasts Are More Accurate Than You Think
Forecasters are better at predicting weather than you are at remembering when they got it right
How Scientists Decide What Counts as Evidence
Why a single study never settles anything—and how scientists build confidence through competing explanations, prior knowledge, and accumulated findings
The Statistics of Rare Disease Clusters: Real Patterns or Random Chance?
How epidemiologists separate genuine environmental hazards from the statistical mirages our pattern-seeking minds inevitably find
How Meta-Analysis Reveals What Individual Studies Cannot
How combining imperfect studies reveals patterns that no single investigation could detect alone
Why Your Intuition About Probability Fails You Every Time
Your brain evolved for savannas, not statistics—here's how to bridge the gap
The Hidden Assumptions Behind Every Statistical Test
Understanding what statistical tests require reveals why so many research findings fail to replicate
The Counterintuitive Logic of Diagnostic Testing
Why a 99% accurate test might still mean you probably don't have the disease
How Scientists Turn Messy Reality into Clean Data
The hidden judgment calls that transform raw observations into the datasets behind scientific conclusions
What Correlation Really Means—And What It Definitely Doesn't
Master the distinction between statistical patterns and genuine causes to evaluate scientific claims with precision.
What Scientists Mean When They Say 'Significant'
Understanding the gap between statistical significance and practical importance transforms how you evaluate every scientific claim you encounter
Why Small Studies Often Show Dramatic Effects That Vanish in Large Trials
How publication selection and sampling noise conspire to inflate early research findings, and the statistical tools that reveal the true effect beneath the hype
How Random Assignment Makes Cause-Effect Conclusions Possible
Discover why flipping a coin creates scientific certainty about cause and effect—and when that certainty crumbles.
The Surprising Math Behind Why Rare Events Seem Common
Understanding why million-to-one odds produce winners daily transforms how you interpret risk, evaluate headlines, and make decisions.
Why Most Published Research Findings Are Wrong—And How to Spot the Valid Ones
Learn the statistical mechanisms behind unreliable research and develop practical tools to distinguish robust science from likely false positives.
How to Read a Scientific Graph Without Being Fooled
Master the visual tricks that distort data and learn to extract truth from scientific figures with confidence
The Art of Asking Questions: How Survey Design Shapes Answers
Discover how question wording, response scales, and survey design invisibly shape the poll numbers that influence public discourse and policy decisions.