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After an event has occurred, people often believe that they could have predicted or perhaps even known with a high degree of certainty what the outcome of the event would be before it occurred. Hindsight bias may cause distortions of memories of what was known or believed before an event occurred and is a significant source of overconfidence in ...
Foresight is the ability to predict, or the action of predicting, what will happen or what is needed in the future. Studies suggest that much of human thought is directed towards potential future events. Because of this, the nature and evolution of foresight is an important topic in psychology. [1]
In a non-statistical sense, the term "prediction" is often used to refer to an informed guess or opinion.. A prediction of this kind might be informed by a predicting person's abductive reasoning, inductive reasoning, deductive reasoning, and experience; and may be useful—if the predicting person is a knowledgeable person in the field.
Scenario analysis is a process of analyzing future events by considering alternative possible outcomes (sometimes called "alternative worlds"). Thus, scenario analysis, which is one of the main forms of projection, does not try to show one exact picture of the future.
The black swan theory or theory of black swan events is a metaphor that describes an event that comes as a surprise, has a major effect, and is often inappropriately rationalized after the fact with the benefit of hindsight. The term is based on a Latin expression which presumed that black swans did not exist. The expression was used until ...
An immutable outcome (e.g., gravity) is difficult to modify cognitively whereas a mutable outcome (e.g., speed) is easier to cognitively modify. Most events lie somewhere in the middle of these extremes. [30] The more mutable the antecedents of an outcome are, the greater availability there is of counterfactual thoughts. [4]
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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]