The “Fourth axiom of probability theory” quickly yields Bayes Theorem – and hence how to deal with inverse probabilities (e.g., P(h|e) versus P(e|h)) – and shows in odds form the importance of likelihood ratios as opposed to simple likelihoods. This paper discusses a problem more basic than ignoring Bayes Theorem. The problem is making no comparisons at all! Just associating. Thus, if P(A|B) or...

Comparing the responses of participants in reasoning experiments to the normative standard of Bayes’ Theorem has been a popular empirical approach for almost half a century. One longstanding finding is that people’s belief revision is conservative with respect to the normative prescriptions of Bayes’ Theorem, that is, beliefs are revised less than they should be. In this paper, we consider a no...

Many clinical decisions are made in uncertainty. When the diagnosis is uncertain, the goal is to establish a diagnosis or to treat even if the diagnosis remains unknown. If the diagnosis is known (e.g., breast cancer or prostate cancer) but the treatment is risky and its outcome uncertain, still a choice must be made. In researching the psychology of clinical judgment and decision making, the m...

This paper shows the availability of using Bayesian classification method to predict class membership probabilities in one deep tight reservoirs Western Desert, Egypt. The workflow our project that used deterministic petrophysical results three training wells train data and extract classifiers. classified were modeled Gaussian distribution for each lithofacies. acquired from a Jurassic gas rese...

This document updates the analysis of errors found in Tina Memo 2010-008. In particular we show that the errors presented there are exact for EML interpretations of parameter estimates, but only an approximation for conventional Likelihood. The work explains the error model used in Tina Memo 2000-007, for the analysis of distribution of cranial fluid as measured in a volumetric segmentation of ...

With the rapid increase of link speed in recent years, packet sampling has become a very attractive and scalable means in collecting flow statistics; however, it also makes inferring original flow characteristics much more difficult. In this paper, we develop techniques and schemes to identify flows with a very large number of packets (also known as heavy-hitter flows) from sampled flow statist...