First-Principles Statistics for Cognitive Bias
Last Updated on February 17, 2026 by Editorial Team
Author(s): Shenggang Li
Originally published on Towards AI.
A practical, model-based way to stop getting fooled by “simple health rules” online
Why do “one simple habit” posts feel so convincing?
This article explores the pitfalls of oversimplified health advice, emphasizing that real-life outcomes are often influenced by multiple factors rather than a single action. It outlines several biases to be wary of, such as the dangers of small sample sizes, selection bias, confounding variables, and interaction effects, all of which can distort our understanding of cause and effect. The piece argues for a deeper engagement with data, advocating for a first-principles approach in statistical thinking to discern genuine insights from misleading claims.
Read the full blog for free on Medium.
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