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 in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

113.4K
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. 
113.4K
Accuracy and Precision01:52

Accuracy and Precision

17.1K
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.  Highly accurate...
17.1K
Accuracy and Precision01:52

Accuracy and Precision

3.1K
3.1K
Random and Systematic Errors01:20

Random and Systematic Errors

15.9K
Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
15.9K
Random and Systematic Errors01:20

Random and Systematic Errors

922
922
Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

671
Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
671

You might also read

Related Articles

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

Sort by
Same author

Investigating the reproducibility of the social and behavioural sciences.

Nature·2026
Same author

Investigating the replicability of the social and behavioural sciences.

Nature·2026
Same author

Investigating the analytical robustness of the social and behavioural sciences.

Nature·2026
Same author

Can a Single Cue Reduce Bias?

Personality & social psychology bulletin·2026
Same author

On the relationship between indirect measures of Black versus White racial attitudes and discriminatory outcomes: An adversarial collaboration using a sample of White Americans.

Journal of personality and social psychology·2026
Same author

A framework for assessing the trustworthiness of scientific research findings.

Proceedings of the National Academy of Sciences of the United States of America·2026

Related Experiment Video

Updated: Mar 21, 2026

An Open Source Technology Platform to Manufacture Hydrogel-Based 3D Culture Models in an Automated and Standardized Fashion
08:29

An Open Source Technology Platform to Manufacture Hydrogel-Based 3D Culture Models in an Automated and Standardized Fashion

Published on: March 31, 2022

5.0K

Scientists' Reputations Are Based on Getting It Right, Not Being Right.

Charles R Ebersole1, Jordan R Axt1, Brian A Nosek1,2

  • 1University of Virginia, Psychology Department, Charlottesville, Virginia, United States of America.

Plos Biology
|May 13, 2016
PubMed
Summary

Scientific replication success or failure impacts scientist reputation based on knowledge pursuit and response to evidence, not just result truth. Opinion favors certainty over exciting uncertainty, highlighting a need for balanced incentives.

More Related Videos

Ole Isacson: Development of New Therapies for Parkinson's Disease
23:53

Ole Isacson: Development of New Therapies for Parkinson's Disease

Published on: April 29, 2007

8.5K
Making Record-efficiency SnS Solar Cells by Thermal Evaporation and Atomic Layer Deposition
14:01

Making Record-efficiency SnS Solar Cells by Thermal Evaporation and Atomic Layer Deposition

Published on: May 22, 2015

43.5K

Related Experiment Videos

Last Updated: Mar 21, 2026

An Open Source Technology Platform to Manufacture Hydrogel-Based 3D Culture Models in an Automated and Standardized Fashion
08:29

An Open Source Technology Platform to Manufacture Hydrogel-Based 3D Culture Models in an Automated and Standardized Fashion

Published on: March 31, 2022

5.0K
Ole Isacson: Development of New Therapies for Parkinson's Disease
23:53

Ole Isacson: Development of New Therapies for Parkinson's Disease

Published on: April 29, 2007

8.5K
Making Record-efficiency SnS Solar Cells by Thermal Evaporation and Atomic Layer Deposition
14:01

Making Record-efficiency SnS Solar Cells by Thermal Evaporation and Atomic Layer Deposition

Published on: May 22, 2015

43.5K

Area of Science:

  • Social Sciences
  • Scientific Integrity
  • Research Ethics

Background:

  • Replication is crucial for scientific accuracy and reliability.
  • The success or failure of replication studies can have significant reputational implications for scientists.
  • Current incentive structures may not adequately balance the rewards for novel discoveries versus rigorous verification.

Purpose of the Study:

  • To investigate how the scientific community and public perceive scientists based on replication outcomes.
  • To explore the factors influencing reputational assessments of scientists involved in replication.
  • To examine the perceived value of certainty versus novelty in scientific findings.

Main Methods:

  • Surveys were conducted with diverse groups: United States adults (N=4,786), undergraduates (N=428), and researchers (N=313).
  • Participants were presented with scenarios comparing scientists based on the certainty and excitement of their results and their response to replication.
  • Reputational assessments were analyzed in relation to these factors.

Main Results:

  • Reputational judgments of scientists were primarily influenced by their approach to knowledge and their reaction to replication evidence, rather than the veracity of their initial findings.
  • When presented with a choice between a scientist with 'boring but certain' results and one with 'exciting but uncertain' results, participants favored the former.
  • This preference for certainty contrasted with the researchers' belief that exciting, uncertain results would be more rewarded.

Conclusions:

  • Scientist reputation is shaped more by the process and response to replication than by the absolute truth of initial findings.
  • There is a societal and potentially scientific preference for certainty, even over exciting but unverified discoveries.
  • Revising incentive systems to equally value both scientific innovation and verification is essential for a robust scientific enterprise.