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

Confidence Interval for Estimating Population Mean01:25

Confidence Interval for Estimating Population Mean

8.8K
A point estimate of the population mean is obtained from a single sample. Such a point estimate does not represent a population well because it needs to account for variability in the population. Single point estimate can also be biased despite the sample being selected randomly. Thus, a point estimate is often unreliable. A confidence interval is needed to reduce this unreliability.
A confidence interval for the mean is a range of values that provides an estimate of the population mean. As the...
8.8K
Confidence Coefficient01:24

Confidence Coefficient

10.5K
The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under...
10.5K
Confidence Intervals01:21

Confidence Intervals

10.2K
An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a  sample proportion. However, unlike the point estimate which is a single value, the confidence interval  contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
A...
10.2K
Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

10.4K
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...
10.4K
Interpretation of Confidence Intervals01:19

Interpretation of Confidence Intervals

9.4K
A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
9.4K
Serial Position Effect01:03

Serial Position Effect

539
The serial position effect is a cognitive phenomenon where individuals are more likely to recall the first and last items in a list compared to those in the middle. This effect is divided into the primacy effect and the recency effect. The primacy effect is observed when the initial items in a list are remembered better. This occurs because these items are rehearsed more frequently or receive more elaborative processing, allowing them to be encoded into long-term memory more effectively. For...
539

You might also read

Related Articles

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

Sort by
Same author

Individual alpha frequency predicts the sensitivity of time perception.

Imaging neuroscience (Cambridge, Mass.)·2026
Same author

Spatial Grouping Modulates the Link between Individual Alpha Frequency and Temporal Integration Windows in Crowding.

Journal of cognitive neuroscience·2026
Same author

Alpha-band phase modulates perceptual sensitivity by changing internal noise and sensory tuning.

eLife·2026
Same author

Effects of TMS on the Decoding and Electrophysiology of Priority in Working Memory.

eNeuro·2026
Same author

Prioritization in working memory reduces interference via a beta band-linked transformation of the not-selected item.

bioRxiv : the preprint server for biology·2026
Same author

Investigating the replicability of the social and behavioural sciences.

Nature·2026
Same journal

Analysis of human visual experience data.

Journal of vision·2026
Same journal

Pyramid-based Bayesian modeling for high-resolution behavioral analysis.

Journal of vision·2026
Same journal

Sensation without perception: The white whale effect and perceptual blindness in autonomous vehicles.

Journal of vision·2026
Same journal

Gaze behavior during closed-captioned movie viewing adapts to absent audio through more frequent switching between text and scene.

Journal of vision·2026
Same journal

In pursuit of saccade awareness: Limited volitional control and minimal conscious access to catch-up saccades during smooth pursuit eye movements.

Journal of vision·2026
Same journal

Dissociable effects of element-lifetime and stimulus-duration on local and global motion processing: An equivalent noise study.

Journal of vision·2026
See all related articles

Related Experiment Video

Updated: Jan 26, 2026

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
12:09

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

Published on: January 8, 2013

14.1K

Confidence boosts serial dependence in orientation estimation.

Jason Samaha1,2, Missy Switzky2, Bradley R Postle3

  • 1University of California, Santa Cruz, Department of Psychology, Santa Cruz, CA.

Journal of Vision
|April 23, 2019
PubMed
Summary
This summary is machine-generated.

Subjective confidence, not just accuracy, influences future decisions. High confidence amplifies the bias from past experiences on current choices, even when accuracy is unrelated.

More Related Videos

On-Chip Crystallization and Large-Scale Serial Diffraction at Room Temperature
07:42

On-Chip Crystallization and Large-Scale Serial Diffraction at Room Temperature

Published on: March 11, 2022

2.3K
Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands
09:04

Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands

Published on: August 29, 2019

14.1K

Related Experiment Videos

Last Updated: Jan 26, 2026

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
12:09

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

Published on: January 8, 2013

14.1K
On-Chip Crystallization and Large-Scale Serial Diffraction at Room Temperature
07:42

On-Chip Crystallization and Large-Scale Serial Diffraction at Room Temperature

Published on: March 11, 2022

2.3K
Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands
09:04

Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands

Published on: August 29, 2019

14.1K

Area of Science:

  • Cognitive psychology
  • Neuroscience
  • Decision-making

Background:

  • Decision-making often relies on subjective confidence when external feedback is absent.
  • Normative models link confidence to signal quality, making it hard to distinguish their independent effects on behavior.
  • Previous research hasn't clearly separated confidence's influence from actual performance accuracy.

Purpose of the Study:

  • To investigate if subjective confidence, independent of task performance, influences future decision-making.
  • To examine the role of confidence in serial dependence, where current estimates are biased by previous stimuli.
  • To determine if confidence amplifies the impact of recent history on perceptual decisions.

Main Methods:

  • Developed visual stimuli to dissociate observer performance from confidence ratings.
  • Measured serial dependence in responses across trials.
  • Compared the strength of serial dependence between high and low confidence decisions, and when confidence was experimentally manipulated.

Main Results:

  • High confidence decisions led to stronger serial dependence on subsequent trials.
  • This effect persisted even when confidence was experimentally dissociated from actual task performance.
  • Subjective confidence, separate from objective accuracy, was found to amplify serial dependence.

Conclusions:

  • Subjective confidence significantly impacts future behavior, independent of actual task accuracy.
  • Perceptual decisions appear to integrate recent history in an uncertainty-weighted manner.
  • The uncertainty influencing future decisions may stem from a subjective, potentially suboptimal, estimate of objective sensory uncertainty.