Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Uncertainty: Overview00:59

Uncertainty: Overview

In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
Propagation of Uncertainty from Random Error00:59

Propagation 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...
Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor 't,' or...
Propagation of Uncertainty from Systematic Error01:10

Propagation 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...
The Uncertainty Principle04:08

The Uncertainty Principle

Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He mathematically...
Significant Figures in Calculations00:58

Significant Figures in Calculations

Uncertainty in measurements can be avoided by reporting the results of a calculation with the correct number of significant figures. This can be determined by the following rules for rounding numbers:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Foundational Aspects for Incorporating Dependencies in Copula-Based Bayesian Networks Using Structured Expert Judgments, Exemplified by the Ice Sheet-Sea Level Rise Elicitation.

Entropy (Basel, Switzerland)·2024
Same author

JAK inhibition with tofacitinib rapidly increases contractile force in human skeletal muscle.

Life science alliance·2024
Same author

Comprehensive evidence implies a higher social cost of CO<sub>2</sub>.

Nature·2022
Same author

Carpal tunnel syndrome and Raynaud's phenomenon: a narrative review.

Occupational medicine (Oxford, England)·2022
Same author

Rationale and design of a mechanistic clinical trial of JAK inhibition to prevent ventilator-induced diaphragm dysfunction.

Respiratory medicine·2021
Same author

Response to letter from Dr M. D. O'Brien.

Occupational medicine (Oxford, England)·2021
Same journal

Toward Resilient Cross-Regional Emergency Governance: A Demand-Driven and Propagation-Based Evolutionary Cooperation Framework.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

Competition and Collaboration in the AI Race: Country-LevelDirectional Evidence for Risk Monitoring and Policy.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

Cyber Resilience: Management With Cybersecurity Controls.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

Jack Fowle: Combining Values, Experience, and Teamwork to Improve Risk Analysis.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

A Hybrid FMEA-AHP Framework for Risk Prioritization in Nontransparent Artificial Intelligence Systems.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

Trust-Building Communication for Extreme Heat Preparedness.

Risk analysis : an official publication of the Society for Risk Analysis·2026
See all related articles

Related Experiment Video

Updated: Jun 17, 2026

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations
09:07

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

Conundrums with uncertainty factors.

Roger Cooke1

  • 1Resources for the Future, Washington, DC, and Department of Mathematics, Delft University of Technology, Delft, The Netherlands. cooke@rff.org

Risk Analysis : an Official Publication of the Society for Risk Analysis
|December 25, 2009
PubMed
Summary
This summary is machine-generated.

Uncertainty factors in risk assessment, particularly for noncancer endpoints, may be overly protective due to strong assumptions. A review suggests probabilistic interpretations and alternative methods like regression models are needed for accurate safety evaluations.

More Related Videos

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
10:22

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Published on: September 7, 2019

Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat
11:18

Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat

Published on: September 12, 2014

Related Experiment Videos

Last Updated: Jun 17, 2026

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations
09:07

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
10:22

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Published on: September 7, 2019

Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat
11:18

Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat

Published on: September 12, 2014

Area of Science:

  • Environmental Health
  • Toxicology
  • Risk Assessment

Background:

  • Traditional safety factors aimed to ensure a "margin of safety" for noncancer endpoints.
  • Modern risk quantification increasingly relies on quantitative risk calculations over safety factors.
  • The IRIS (Integrated Risk Information System) database utilizes uncertainty factors in its assessments.

Purpose of the Study:

  • To critically evaluate the probabilistic interpretation and application of uncertainty factors in risk assessment.
  • To explore whether current uncertainty factor practices are overly protective based on probabilistic arguments.
  • To propose alternative methodologies for a more accurate assessment of uncertainty in risk calculations.

Main Methods:

  • Review of probabilistic arguments regarding the interpretation of uncertainty factors.
  • Analysis of assumptions underlying the application of uncertainty factors, such as extrapolation from animal to human.
  • Exploration of alternative statistical approaches, including standard regression models and Bayesian belief nets.

Main Results:

  • Probabilistic interpretations suggest uncertainty factors may entail strong, potentially unrealistic assumptions about response rates.
  • These assumptions can lead to an ill-conditioned analysis, computing uncertainty conditional on zero probability.
  • The current practice of uncertainty factors may be overly protective, necessitating a re-evaluation.

Conclusions:

  • The application of uncertainty factors in risk assessment warrants a thorough review.
  • Probabilistic approaches and advanced statistical models offer potential improvements over traditional methods.
  • Alternative methods like regression and Bayesian belief nets could provide more robust uncertainty analyses.