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The least dangerous assumption is an inclusive approach to educational policy and pedagogy. It holds that, "in the absence of conclusive data, educational decisions should be based on assumptions which, if incorrect, will have the least dangerous effect on the student".
If a fair coin lands on heads 10 times in a row, the belief that it is "due to the number of times it had previously landed on tails" is incorrect. [61] Inverse gambler's fallacy – the inverse of the gambler's fallacy. It is the incorrect belief that on the basis of an unlikely outcome, the process must have happened many times before.
Another feature of an argument based on false premises that can bedevil critics, is that its conclusion can in fact be true. Consider the above example again. It may well be that it has recently rained and that the streets are wet. This does nothing to prove the first premise, but can make its claims more difficult to refute.
An exception is analytic philosopher John Searle, who called it an incorrect assumption that produces false dichotomies. Searle insists that "it is a condition of the adequacy of a precise theory of an indeterminate phenomenon that it should precisely characterize that phenomenon as indeterminate; and a distinction is no less a distinction for ...
An example is a probabilistically valid instance of the formally invalid argument form of denying the antecedent or affirming the consequent. [ 12 ] Thus, "fallacious arguments usually have the deceptive appearance of being good arguments, [ 13 ] because for most fallacious instances of an argument form, a similar but non-fallacious instance ...
For example, if the p-value of a test statistic result is estimated at 0.0596, then there is a probability of 5.96% that we falsely reject H 0. Or, if we say, the statistic is performed at level α, like 0.05, then we allow to falsely reject H 0 at 5%. A significance level α of 0.05 is relatively common, but there is no general rule that fits ...
The gambler's fallacy, also known as the Monte Carlo fallacy or the fallacy of the maturity of chances, is the belief that, if an event (whose occurrences are independent and identically distributed) has occurred less frequently than expected, it is more likely to happen again in the future (or vice versa).
In the context of knowledge management, the closed-world assumption is used in at least two situations: (1) when the knowledge base is known to be complete (e.g., a corporate database containing records for every employee), and (2) when the knowledge base is known to be incomplete but a "best" definite answer must be derived from incomplete information.