Why We Only Hear About The Winners? Survivorship Bias Explained | FutureIQ
Concepts in this episode
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Selection Bias mechanism
Selection bias occurs when the path into a sample systematically excludes cases, making patterns produced by that filter look like properties of the wider world. Before trusting a relationship, reconstruct how each observed case became visible.
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Survivorship Bias mental-model
Survivorship bias appears when visible successes are mistaken for the whole sample. Once failures disappear from view, success looks easier, predictions look stronger, and the past looks kinder than the evidence warrants.
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Fooled by Randomness mental-model
A streak of success can arise from randomness when enough attempts run in parallel. Before calling the survivor skilled, reconstruct the losing field and ask what chance alone would produce.
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Post Hoc Ergo Propter Hoc mental-model
Sequential stories feel causal because the mind turns “after this” into “because of this.” The real test is whether the intervention made recovery more likely than it would have been without the intervention.
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Correlation vs Causation principle
Observed association is evidence to investigate, not proof of causal power. A credible causal claim needs comparison cases and a mechanism that can distinguish causation from confounding, reverse direction, and coincidence.
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Narrative Fallacy mental-model
Humans prefer coherent stories to messy statistical explanations, so selected successes and random sequences are easily mistaken for causes. A story can generate a hypothesis, but it cannot establish one.
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Alpha domain
Alpha is return above a relevant market benchmark after broad market gains, luck, and noise are removed. It is rare because a durable edge usually requires costly information or disciplined analysis, not tips validated by a visible winner.
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