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For example, explanatory power over all existing observations (criterion 3) is satisfied by no one theory at the moment. [ 10 ] Whatever might be the ultimate goals of some scientists, science, as it is currently practiced, depends on multiple overlapping descriptions of the world, each of which has a domain of applicability.
One can use language to describe a model; however, the theory is the model (or a collection of similar models), and not the description of the model. A model of the solar system, for example, might consist of abstract objects that represent the sun and the planets. These objects have associated properties, e.g., positions, velocities, and masses.
Carl Sagan, seen here with a model of Viking lander, popularized the aphorism. "Extraordinary claims require extraordinary evidence" (sometimes shortened to ECREE), [1] also known as the Sagan standard, is an aphorism popularized by science communicator Carl Sagan. He used the phrase in his 1979 book Broca's Brain and the 1980 television ...
[1] [2] Hierarchy of study design, for example using a case-study, ecological study, cross-sectional, case-control, cohort, or experimental, although not always in this order is a general rule to a high "strength of evidence" of a clinical study. [3] [4] [5]
Such evidence is expected to be empirical evidence and interpretable in accordance with the scientific method. Standards for scientific evidence vary according to the field of inquiry, but the strength of scientific evidence is generally based on the results of statistical analysis and the strength of scientific controls. [citation needed]
In philosophy of science, strong inference is a model of scientific inquiry that emphasizes the need for alternative hypotheses, rather than a single hypothesis to avoid confirmation bias. The term "strong inference" was coined by John R. Platt , [ 1 ] a biophysicist at the University of Chicago .
While most mathematicians do not think that probabilistic evidence for the properties of a given object counts as a genuine mathematical proof, a few mathematicians and philosophers have argued that at least some types of probabilistic evidence (such as Rabin's probabilistic algorithm for testing primality) are as good as genuine mathematical ...
Arthur P. Dempster at the Workshop on Theory of Belief Functions (Brest, 1 April 2010).. The theory of belief functions, also referred to as evidence theory or Dempster–Shafer theory (DST), is a general framework for reasoning with uncertainty, with understood connections to other frameworks such as probability, possibility and imprecise probability theories.