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<p>This commentary discusses Shiffrin, Stigler, and Keil (2025) on illusions of understanding in science, focusing on linear regression as a key example where predictive success is often mistaken for causal insight. It highlights how statistical paradoxes and specification issues reveal the gap between formal accuracy and true understanding, and extends the discussion to pedagogical and sociological factors that reinforce these illusions.</p>

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Commentary on Illusions of Understanding in the Sciences

  • 期刊论文

  • 发表日期：

    2026年4月15日

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  • Moawia Alghalith

摘要

This commentary discusses Shiffrin, Stigler, and Keil (2025) on illusions of understanding in science, focusing on linear regression as a key example where predictive success is often mistaken for causal insight. It highlights how statistical paradoxes and specification issues reveal the gap between formal accuracy and true understanding, and extends the discussion to pedagogical and sociological factors that reinforce these illusions.