PPT-4 : Uncertainty and Probability

The scientist has a lot of experience with ignorance and doubt and uncertainty and this experience is of very great importance I think When a scientist does not know the answer to a problem he is ignorant When he has a hunch as to what the result is he is uncertain And when he is pretty damn sure of what the result is going to be he is still in some doubt. Jake Blanchard. Spring 2010. Uncertainty Analysis for Engineers. 1. Random Variables. We will spend the rest of the semester dealing with random variables. A random variable is a function defined on a particular sample space. Jake Blanchard. Spring . 2010. Uncertainty Analysis for Engineers. 1. Introduction. Probability plots allow us to assess the degree to which a set of data fits a particular distribution. The idea is to scale the x-axis of a CDF such that the result would be a straight line if the data conforms to the assumed distribution. Lack of knowledge vs. variability.. What type of safety measures do we take?. Design, manufacturing, operations & post-mortems. Living with uncertainties vs. changing them. How do we represent random variables?. Lack of knowledge vs. variability.. What type of safety measures do we take?. Design, manufacturing, operations & post-mortems. Living with uncertainties vs. changing them. How do we represent random variables?. Jake Blanchard. Spring 2010. Uncertainty Analysis for Engineers. 1. Introduction. Interpretations of Probability. Classical – If an event can occur in N equally likely and different ways, and if n of these have an attribute A, then the probability of the occurrence of A, denoted Pr(A), is defined as n/N. 1. 2. 3. Intelligent user interfaces. Communication codes. Protein sequence alignment. Object tracking. 4. Stopping distance (95% confidence interval). Braking initiated. Gradual stop. Success stories…. “The . Human Factor in . Risk”. London. 8–9 . September 2012. The Philosophy of . Risk. Martin . Sewell. Risk. In my (Bayesian) mind, . risk. . is . uncertainty.. U. ncertainty. . is best described using a probability distribution, and the broader the distribution, the greater the uncertainty. Lack of knowledge vs. variability.. What type of measures do we take to reduce uncertainty?. Design, manufacturing, operations & post-mortems. Living with uncertainties vs. changing them. How do we represent random variables?. 1. 2. 3. Intelligent user interfaces. Communication codes. Protein sequence alignment. Object tracking. 4. Stopping distance (95% confidence interval). Braking initiated. Gradual stop. Success stories…. Survival Under Uncertainty. An Introduction to Probability Models of Social Evolution. State secession in 1800-2014. The . mean lifetime of a state . is . 122 . years;. Half–life of a state . 4. Introduction. (slide 1 of 3). A key . aspect of solving real business problems is dealing appropriately with uncertainty.. This involves recognizing explicitly that uncertainty exists and using quantitative methods to model uncertainty.. . Tahmasebi. . and . Jef. . Caers. Updating joint uncertainty in trend and depositional models for exploration and early appraisal stage. Only 1 well, no production yet. Low quality 3D seismic. How to model properly uncertainty in . Uncertainty. Irreducible uncertainty . is inherent to a system. Epistemic uncertainty . is caused by the subjective lack of knowledge by the algorithm designer. In optimization problems, uncertainty can be represented by a vector of random variables . Richard J. Nugent III, Ph.D. . Economist, HEC-FDA Lead. Hydrologic Engineering Center . Davis, CA. agenda. What is flood risk, and how do we describe it?. How do we assess flood risk?. What goes into the uncertainty about flood risk?.