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English -- Keynote Lectures

contributor authorASCE - American Society of Civil Engineers
date accessioned2017-10-18T11:08:01Z
date available2017-10-18T11:08:01Z
date copyright2017.01.01
date issued2017
identifier otherVCEVZFAAAAAAAAAA.pdf
identifier urihttp://yse.yabesh.ir/std/handle/yse/235439
description abstractScope: The statistics course most of us took in college introduced a peculiar and narrow species of the subject. Indeed, that species of statistics—usually called, Relative Frequentist theory—is not of much use in grappling with the problems geotechnical engineers routinely face. The sampling theory approach to statistics that arose in the early 20th C. has to do with natural variations within well-defined populations. It has to do with frequencies like the flipping of a coin. Geotechnical engineers, in contrast, deal with uncertainties associated with limited knowledge. They have to do with the probabilities of unique situations. These uncertainties are not amenable to Frequentist thinking; they require Bayesian thinking. Bayesian thinking is that of judgment and belief. It leads to remarkably strong inferences from even sparse data. Most geotechnical engineers are intuitive Bayesians whether they know it or not, and have much to gain from a more formal understanding of the logic behind these straightforward and relatively simple methods.
languageEnglish
titleASCE GSP 282num
titleEnglish -- Keynote Lecturesen
typestandard
page163
statusActive
treeASCE - American Society of Civil Engineers:;2017
contenttypefulltext


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