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Bayesian statistics are based on a different philosophical approach for proof of inference.The mathematical formula for Bayes's theorem is: [|] = [|] [] []The formula is read as the probability of the parameter (or hypothesis =h, as used in the notation on axioms) “given” the data (or empirical observation), where the horizontal bar refers to "given".
The origin of the phrase "Lies, damned lies, and statistics" is unclear, but Mark Twain attributed it to Benjamin Disraeli [1] "Lies, damned lies, and statistics" is a phrase describing the persuasive power of statistics to bolster weak arguments, "one of the best, and best-known" critiques of applied statistics. [2]
To show that a conclusion is underdetermined, one must show that there is a rival conclusion that is equally well supported by the standards of evidence. A trivial example of underdetermination is the addition of the statement "whenever we look for evidence" (or more generally, any statement which cannot be falsified). For example, the ...
The "thesis statement" comes from the concept of a thesis (θέσῐς, thésis) as it was articulated by Aristotle in Topica. Aristotle's definition of a thesis is "a conception which is contrary to accepted opinion." He also notes that this contrary view must come from an informed position; not every contrary view is a thesis. [3]
The conclusion of an argument is true if the argument is sound, which is to say if the argument is valid and its premises are true. By contrast, "scientific or statistical validity" is not a deductive claim that is necessarily truth preserving, but is an inductive claim that remains true or false in an undecided manner.
The uniqueness thesis is “the idea that a body of evidence justifies at most one proposition out of a competing set of propositions (e.g., one theory out of a bunch of exclusive alternatives) and that it justifies at most one attitude toward any particular proposition.” [1] The types of attitudes towards a proposition, are: believing, disbelieving, and suspending judgment.
If one wishes to prove a statement, not for all natural numbers, but only for all numbers n greater than or equal to a certain number b, then the proof by induction consists of the following: Showing that the statement holds when n = b. Showing that if the statement holds for an arbitrary number n ≥ b, then the same statement also holds for n ...
In the theory of probability, the Glivenko–Cantelli theorem (sometimes referred to as the Fundamental Theorem of Statistics), named after Valery Ivanovich Glivenko and Francesco Paolo Cantelli, describes the asymptotic behaviour of the empirical distribution function as the number of independent and identically distributed observations grows. [1]