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相关概念视频

Uncertainty: Overview00:59

Uncertainty: Overview

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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.
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Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

81.5K
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. 
81.5K
Prediction Intervals01:03

Prediction Intervals

2.3K
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. 
2.3K
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

1.1K
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...
1.1K
Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

4.8K
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...
4.8K
Hindsight Biases01:12

Hindsight Biases

3.9K
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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相关实验视频

Updated: Sep 14, 2025

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations
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估计不确定性会影响有或没有学习机会的决策.

Kristoffer C Aberg1,2, Levi Antle3,4, Rony Paz5,6

  • 1Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel. kc.aberg@gmail.com.

Nature communications
|July 21, 2025
PubMed
概括

估计不确定性,选择样本的频率,即使没有新的学习机会,也会影响长期决策. 这种抽样偏差仍然存在,影响选择的选择与强化学习的预期结果无关.

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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
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The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies

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科学领域:

  • 认知神经科学 认知神经科学
  • 行为经济学是一种行为经济学.
  • 计算神经科学是一种神经科学.

背景情况:

  • 强化学习 (RL) 涉及结果预期和估计不确定性,这影响了探索.
  • 在没有进一步学习或探索的情况下,估计不确定性对决策的长期影响仍然不清楚.

研究的目的:

  • 调查强化学习阶段的估计不确定性是否会在没有反的情况下影响后续决策.
  • 要确定这种效应是否独立于结果预期.

主要方法:

  • 进行了强化学习阶段与反.
  • 随后的测试阶段没有反评估决策偏见.
  • 使用计算建模来适应行为数据.

主要成果:

  • 在学习过程中获得的采样率与测试阶段的决策偏差相关.
  • 估计不确定性改进了计算模型的匹配,特别是在样本较少的选项中.
  • 结果在两个独立的数据集中复制.

结论:

  • 在强化学习过程中获得的估计不确定性可以产生持久的决策偏见.
  • 这种偏见是独立于结果预期的.
  • 估计不确定性是理解人类决策的关键因素.