Titlebook: Statistics and Probability Theory; In Pursuit of Engine Michael Havbro Faber Book 2012 Springer Science+Business Media B.V. 2012 Bayesian p

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Basic Probability Theory,rtant result forms the mathematical framework for synthesizing information into knowledge. The chapter is concluded by two examples illustrating how the rule of Bayes may be applied to quantify the knowledge acquired by collection of information in the context of condition and load carrying capacity

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Descriptive Statistics,t methods of descriptive statistics are illustrated throughout the chapter by means of data from experiments concerning the compression strength of concrete test specimens as well as road way traffic observations.

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Uncertainty Modeling,s and results of special importance in probabilistic engineering modeling are presented including the expectation operator, random vectors and joint moments, conditional distributions and conditional moments, the distribution of the sum of two random variables and the distribution of functions of ra

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Estimation and Model Building,the choice of distribution type, it is then shown how the Method of Moments and the Maximum Likelihood Method, together with available observations, may be utilized to estimate the corresponding probability distribution parameters..In Lecture 9, it is shown how engineering models may be established

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Methods of Structural Reliability,the probability of interest may be determined in terms of the reliability index and the cumulative standard Normal distribution. Then, on this basis, the generalization to non-linear safety margins is made and the classical error propagation law is introduced as a means of approximating the reliabil

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pment of stable pharmaceutical suspensionsThe suspension dosage form has long been used for poorly soluble active ingre- ents for various therapeutic indications. Development of stable suspensions over the shelf life of the drug product continues to be a challenge on many fronts. A good understandin

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