Welcome to NUSAP net Glossary|
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||Validation is the process of comparing model output with observations
of the 'real world'. Validation can not 'validate' a model as true or
correct, but can help establish confidence in a model's utility in
cases where the samples of model output and real world samples are at
least not inconsistent. For a fuller discussion of issues in
validation, see Oreskes et al., (1994).|
||Value-ladenness refers to the notion that value orientations and biases of an analyst, an institute,
a discipline or a culture can co-shape the way scientific questions are framed,
data are selected, interpreted, and rejected, methodologies are devised, explanations are formulated
and conclusions are formulated. Since theories are always underdetermined by
observation, the analysts' biases will fill the epistemic gap which makes any assessment
to a certain degree value-laden.|
||In one meaning of the word, variability refers to the observable variations (e.g. noise) in a quantity that result from randomness in nature (as in 'natural variability of climate') and society. |
In a slightly different meaning, variability refers to heterogeneity across space, time or members of a population.
Variability can be expressed in terms of the extent to which the scores in a distribution of a quantity differ from each other.
Statistical measures for variability include the range, mean deviation from the mean, variance, and standard deviation.
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