Related Experiment Videos
Representation, propagation, and decision issues in risk analysis under incomplete probabilistic information
1IRIT,Université Paul Sabatier, 31062 Toulouse Cedex, France. dubois@irit.fr
Summary
Uncertainty theories like imprecise probabilities enhance risk analysis by integrating objective data with subjective expert judgment. These methods offer more expressive tools for handling incomplete information in risk assessment.
Area of Science:
- Decision Sciences
- Risk Management
- Artificial Intelligence
Background:
- Traditional risk analysis often relies on either purely objective, statistically founded probability distributions or subjective expert judgment.
- Handling incomplete information in risk assessment presents challenges for existing methodologies.
- There is a need for more expressive tools to represent and manage uncertainty.
Purpose of the Study:
- To clarify the role of uncertainty theories, including imprecise probabilities, random sets, and possibility theory, in risk analysis.
- To advocate for the articulation of objective and subjective approaches in risk assessment.
- To demonstrate that risk analysis under incomplete information is not purely objective.
Main Methods:
- Review and synthesis of uncertainty theories (imprecise probabilities, random sets, possibility theory).
- Conceptual framework for articulating objective and subjective risk analysis.
- Examination of the application of these theories to uncertainty elicitation, propagation, and decision-making.
Main Results:
- Uncertainty theories provide more expressive representation tools than simple probability distributions or intervals.
- These theories can effectively capture expert judgments while respecting their inherent imprecision.
- A combined approach of objective and subjective analysis, facilitated by uncertainty theories, is more robust.
Conclusions:
- Uncertainty theories are crucial for a comprehensive risk analysis process, especially under incomplete information.
- Integrating diverse uncertainty representation tools enhances the fidelity and utility of risk assessments.
- The proposed framework supports improved decision-making by better characterizing and managing risks.
Related Concept Videos
00:59Propagation of Uncertainty from Random Error
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
01:10Propagation of Uncertainty from Systematic Error
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this particular...
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
01:14Probability in Statistics
Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
01:11Hazard Rate
The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
01:32Probability Distributions
The probability of a random variable x is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson probability...
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson probability...