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Plausible reasoning is based on the way things generally go in familiar situations. Plausible reasoning can be used to fill in implicit premises in incomplete arguments. Plausible reasoning is commonly based on appearances from perception. Stability is an important characteristic of plausible reasoning. Plausible reasoning can be tested, and by ...
A knowledge base of facts and rules is needed, but some of them may be uncertain because there may be a probability associated to using them for inference. Therefore, we can also refer to this as plausible inference. The plausibility of an inference is a function of the plausibility of each query assertion. Rather than retrieving a document ...
For example, a tsunami could also explain why the streets are wet but this is usually not the best explanation. As a form of non-deductive reasoning, abduction does not guarantee the truth of the conclusion even if the premises are true. [80] [82] The more plausible the explanation is, the stronger it is supported by the premises.
In statistics education, informal inferential reasoning (also called informal inference) refers to the process of making a generalization based on data (samples) about a wider universe (population/process) while taking into account uncertainty without using the formal statistical procedure or methods (e.g. P-values, t-test, hypothesis testing, significance test).
Third, commonsense reasoning involves plausible reasoning. It requires coming to a reasonable conclusion given what is already known. Plausible reasoning has been studied for many years and there are a lot of theories developed that include probabilistic reasoning and non-monotonic logic. It takes different forms that include using unreliable ...
Examples include people of many different non-open political ideologies, despite their enmity to each other, having a shared belief that it is "ethical" to give an appearance of humans justifying beliefs and "unethical" to admit that humans are open-minded in the absence of threats that inhibit critical thinking, making them fake justifications.
For example, If P, then Q. P. ∴ Q. In this example, the first premise is a conditional statement in which "P" is the antecedent and "Q" is the consequent. The second premise "affirms" the antecedent. The conclusion, that the consequent must be true, is deductively valid.
Mathematics and Plausible Reasoning is a two-volume book by the mathematician George Pólya describing various methods for being a good guesser of new mathematical results. [ 1 ] [ 2 ] In the Preface to Volume 1 of the book Pólya exhorts all interested students of mathematics thus: "Certainly, let us learn proving, but also let us learn guessing."