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

The Uncertainty Principle04:08

The Uncertainty Principle

35.1K
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...
35.1K
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

2.2K
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...
2.2K
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

1.6K
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...
1.6K
Uncertainty: Overview00:59

Uncertainty: Overview

1.9K
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.
1.9K
Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

12.7K
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...
12.7K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

114.0K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
114.0K

You might also read

Related Articles

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

Sort by
Same author

Interprofessional Education Between Undergraduate Medical and Midwifery Students: A Mixed-Methods Systematic Review.

Journal of medical education and curricular development·2026
Same author

Impact of artificial intelligence integrations on empathy in healthcare interactions between patients and practitioners: protocol for a systematic review and thematic synthesis of qualitative studies.

BMJ open·2026
Same author

Therapeutic empathy in remote consultations in general practice: a realist review protocol.

BMJ open·2026
Same author

Complex intervention to improve empathy within maternity services: a mixed methods feasibility study with pilot evaluation.

BMJ open quality·2026
Same author

The impacts of high-fidelity and virtual reality simulation on the development of non-technical skills in healthcare students and professionals: protocol for a systematic review.

BMJ open·2026
Same author

Novel approach to teaching empathic leadership using heuristics.

BMJ leader·2026

Related Experiment Video

Updated: Apr 19, 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

9.5K

In search of justification for the unpredictability paradox.

Jeremy Howick1, Alexander Mebius

  • 1Department of Primary Care Health Sciences, University of Oxford, New Radcliffe House, 2nd floor, Oxford OX2 6NW, UK. jeremy.howick@phc.ox.ac.uk.

Trials
|December 11, 2014
PubMed
Summary

Adequate randomization in clinical trials does not consistently alter effect sizes compared to inadequate randomization. The "unpredictability paradox" is problematic, hindering falsifiable conclusions and research into randomization

More Related Videos

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

15.9K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

3.1K

Related Experiment Videos

Last Updated: Apr 19, 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

9.5K
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

15.9K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

3.1K

Area of Science:

  • Clinical Trials Methodology
  • Evidence-Based Medicine
  • Research Integrity

Background:

  • A 2011 Cochrane Review examined the impact of randomization quality on trial effect sizes.
  • The review found no average statistically significant difference between adequately and inadequately randomized trials.

Purpose of the Study:

  • Critique the
  • unpredictability paradox
  • postulated by the 2011 Cochrane Review authors.

Main Methods:

  • Analysis of findings from the 2011 Cochrane Review.
  • Evaluation of the logical and practical implications of the
  • unpredictability paradox
  • .

Main Results:

  • Adequate randomization did not show a consistent effect on trial outcome magnitudes.
  • The
  • unpredictability paradox
  • renders conclusions about randomization's impact unfalsifiable.
  • This paradox complicates meta-analysis and discourages further investigation into randomization's nuances.

Conclusions:

  • The
  • unpredictability paradox
  • is a problematic concept in clinical trial methodology.
  • It obscures the potential importance of other bias-mitigation strategies like allocation concealment and blinding.
  • Further research is needed to understand the conditions influencing randomization's effect on treatment benefit exaggeration.