randomness quantification
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Data-based information which is characterized by random fluctuations may be described with the aid of a traditional probabilistic model.
This is associated with certain requirements, e.g., regarding reproduction conditions or compliance with the i.i.d. paradigm (identically, independently distributed). If all the conditions are met, the entire variety of mathematical statistics with its established methods from estimation and test theory can be employed to specify and to quantify the uncertainty. The desire for considering well-defined subjective assessments in terms of probability requires an extended probabilistic model. As a basis, the model of subjective probability, in particular, in the form of a Bayesian approach is frequently proposed for this purpose.
References
- Wright, G (1994) Subjective probability, Wiley, Chichester.
- Bernardo, JM, and Smith, AF (1994) Bayesian Theory, Wiley, Chichester New York Brisbane Toronto Singapore.
- Mood, AM, Graybill, FA, and Boes, DC (1974) Introduction to the Theory of Statistics, McGraw-Hill, New York.
- Benjamin, JR, and Cornell, CA (1970) Probability, Statistics and Decision for Civil Engineers, McGraw-Hill, New York.
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