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  2. Predictive modelling - Wikipedia

    en.wikipedia.org/wiki/Predictive_modelling

    Predictive modelling uses statistics to predict outcomes. [1] Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place. [2]

  3. Hindsight bias - Wikipedia

    en.wikipedia.org/wiki/Hindsight_bias

    The role of surprise can help explain the malleability of hindsight bias. Surprise influences how the mind reconstructs pre-outcome predictions in three ways: 1. Surprise is a direct metacognitive heuristic to estimate the distance between outcome and prediction. 2. Surprise triggers a deliberate sense-making process. 3.

  4. Foreshadowing - Wikipedia

    en.wikipedia.org/wiki/Foreshadowing

    Foreshadowing only hints at a possible outcome within the confinement of a narrative and leads readers in the right direction. A flashforward is a scene that takes the narrative forward in time from the current point of the story in literature, film, television, or other media.

  5. 'Why I was wrong': Allan Lichtman fails to predict correct ...

    www.aol.com/why-wrong-allan-lichtman-fails...

    He was wrong. Or so the American people decided.. Allan Lichtman, the historian who predicted 9 of the 10 last elections, failed to accurately predict who voters would chose to become the 47th ...

  6. Black swan theory - Wikipedia

    en.wikipedia.org/wiki/Black_swan_theory

    More generally, decision theory, which is based on a fixed universe or a model of possible outcomes, ignores and minimizes the effect of events that are "outside the model". For instance, a simple model of daily stock market returns may include extreme moves such as Black Monday (1987) , but might not model the breakdown of markets following ...

  7. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    The core of predictive analytics relies on capturing relationships between explanatory variables and the predicted variables from past occurrences, and exploiting them to predict the unknown outcome. It is important to note, however, that the accuracy and usability of results will depend greatly on the level of data analysis and the quality of ...

  8. Axelrod won’t predict election outcome: ‘I’d be a fool to ...

    www.aol.com/axelrod-won-t-predict-election...

    Democratic strategist David Axelrod said he would be a “fool” to try to predict the outcome of the 2024 election, arguing that the polling margins he’s seen are “way too close to call ...

  9. Why prediction markets can be more accurate than polls at ...

    www.aol.com/why-prediction-markets-more-accurate...

    Prediction markets can be more accurate than polling when it comes to elections, a professor told Business Insider. There's over $606 million wagered on the 2024 election on Polymarket, favoring a ...