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The validity of a measurement tool (for example, a test in education) is the degree to which the tool measures what it claims to measure. [3] Validity is based on the strength of a collection of different types of evidence (e.g. face validity, construct validity, etc.) described in greater detail below.
In statistics, the observed information, or observed Fisher information, is the negative of the second derivative (the Hessian matrix) of the "log-likelihood" (the logarithm of the likelihood function). It is a sample-based version of the Fisher information.
Likelihoodist statistics is a more minor school than the main approaches of Bayesian statistics and frequentist statistics, but has some adherents and applications. The central idea of likelihoodism is the likelihood principle : data are interpreted as evidence , and the strength of the evidence is measured by the likelihood function.
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".
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]
[1] [2] [3] Construct validation is the accumulation of evidence to support the interpretation of what a measure reflects. [ 1 ] [ 4 ] [ 5 ] [ 6 ] Modern validity theory defines construct validity as the overarching concern of validity research, subsuming all other types of validity evidence [ 7 ] [ 8 ] such as content validity and criterion ...
Examples of observer bias extend back to the early 1900's. One of the first recorded events of apparent observer bias was seen in 1904, with the case of "Clever Hans". Clever Hans was a horse whose owner, Wilhem von Olson, claimed could solve arithmetic equations. Von Olson would ask Clever Hans a series of questions involving arithmetic ...
In some specific fields of science, the results of observation differ depending on factors that are not important in everyday observation. These are usually illustrated with apparent " paradoxes " in which an event appears different when observed from two different points of view, seeming to violate "common sense".