Quantifying Statistical Uncertainty in Site Investigation

Quantifying Statistical Uncertainty in Site Investigation

Ching, J.
Wu, S.-H
Phoon, K.-K.

2015-10-15

Due to limited information in site investigation, it is not possible to obtain the actual values for the mean, standard deviation, and scale of fluctuation of a soil property of interest. The deviation between the estimated values and actual values is called the statistical uncertainty. There are two schools of thoughts on how to model the statistical uncertainty: frequentist thought and Bayesian thought. The purpose of this paper is to discuss their philosophical difference, to show how to quantify the statistical uncertainty based on these two distinct schools of thoughts, and to compare their performances. For the frequentist school of thought, the confidence interval will be used to quantify the statistical uncertainty, whereas the posterior probability distribution will be used for the Bayesian school of thought. Examples will be presented to compare the performances of these two schools of thoughts in terms of their consistencies. The results show that in general the Bayesian school of thought performs better in terms of consistency. In particular, the Markov chain Monte Carlo method is recommended when the information amount is very limited.

statistical uncertainty
site investigation
frequentist
Bayesian
reliability

http://resolver.tudelft.nl/uuid:56072316-266d-45f3-b0a9-4e716dffe8b0

https://doi.org/10.3233/978-1-61499-580-7-933

Conference proceedings

conference paper

(c) 2015 The Authors and IOS Press, Creative Commons CC-BY