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Related Concept Videos

Prediction Intervals01:03

Prediction Intervals

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The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
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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...
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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...
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Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
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Errors In Hypothesis Tests01:14

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Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
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Related Experiment Video

Updated: Mar 1, 2026

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers
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A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

Published on: January 5, 2018

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Does prediction error drive one-shot declarative learning?

Andrea Greve1, Elisa Cooper1, Alexander Kaula1

  • 1MRC Cognition & Brain Sciences Unit, Cambridge, England, United Kingdom.

Journal of Memory and Language
|June 6, 2017
PubMed
Summary
This summary is machine-generated.

Prediction error, the difference between expected and actual outcomes, enhances learning. This study shows prediction error improves one-shot declarative memory encoding by manipulating prior expectations and sensory evidence.

Keywords:
Associative memoryEncodingOne-shot learningPrediction error

Related Experiment Videos

Last Updated: Mar 1, 2026

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers
08:05

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

Published on: January 5, 2018

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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Memory Research

Background:

  • Prediction error (PE) is crucial for learning in various domains.
  • Its role in human one-shot declarative encoding remains less understood.
  • A hypothesis posits PE reflects divergence between prior and sensory evidence distributions.

Purpose of the Study:

  • To investigate the role of prediction error in human one-shot declarative encoding.
  • To test how manipulating prior probability, prior precision, and evidence precision affects memory.
  • To determine if prediction error enhances the encoding of novel scene-item pairings.

Main Methods:

  • Five experiments manipulated prediction error factors: prior-evidence distance, prior precision, and evidence precision.
  • Participants encoded single scene-item pairings after varying prior exposures.
  • Memory was tested using a three-choice recognition task.

Main Results:

  • Inconsistent evidence with prior expectations enhanced memory, supporting higher PE.
  • More precise priors, when inconsistent, led to better memory.
  • Increased sensory evidence precision also improved memory.
  • All experiments supported the prediction error hypotheses.

Conclusions:

  • Prediction error significantly enhances one-shot declarative memory encoding.
  • The Predictive Interactive Multiple Memory Signals (PIMMS) framework parsimoniously explains the findings.
  • Findings clarify the role of prediction error in forming new memories.