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関連する概念動画

Uncertainty: Overview00:59

Uncertainty: Overview

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.
Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

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 't,' or...
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

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...
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

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 particular...
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
Counterfactual Thinking01:19

Counterfactual Thinking

Counterfactual thinking is a cognitive process wherein individuals mentally reconstruct alternative versions of past events, often beginning with “what if” or “if only.” This reflective mechanism plays a significant role in shaping emotional experiences and guiding future behavior. Though typically triggered by unfavorable or unexpected outcomes, counterfactual thinking can also emerge in mundane, everyday decisions and experiences, revealing its deep entrenchment in human cognition.Types of...

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Using Generative Art to Convey Past and Future Climate Transitions
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Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

未来に関する不確実性を視覚化する.

David Spiegelhalter1, Mike Pearson, Ian Short

  • 1Centre for Mathematical Sciences, University of Cambridge, Cambridge CB3 0WB, UK. d.spiegelhalter@statslab.cam.ac.uk

Science (New York, N.Y.)
|September 10, 2011
PubMed
まとめ
この要約は機械生成です。

不確実性を視覚的に伝えるのは難しい. インタラクティブビジュアライゼーションは潜在的可能性を秘めているが,複雑な不確実性や論争の的不確実性を公衆に効果的に伝えることは,依然として大きな障害となっている.

さらに関連する動画

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations
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Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

関連する実験動画

Last Updated: May 29, 2026

Using Generative Art to Convey Past and Future Climate Transitions
06:10

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

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

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

科学分野:

  • データ可視化 データ可視化
  • リスクコミュニケーション リスクコミュニケーション
  • コグニティブ・サイエンス コグニティブ・サイエンス

背景:

  • 未来に関する不確実性は広く存在し,確率はいくつかの側面を定量化する方法を提供します.
  • これらの確率を一般大衆に効果的に伝えることは,既知の課題です.
  • ビジュアライゼーションはますます使用されていますが,その理解に関する証拠は限られています.

研究 の 目的:

  • 不確実性を視覚的に伝達する現在の慣行を見直す.
  • 様々な領域における異なるビジュアライゼーションタイプの有効性を検証する.
  • 不確実性のより深い形態を伝達する際の課題を特定する.

主な方法:

  • 不確実性の可視化における現在の実践に関する文献レビュー.
  • 天気,健康,経済などのさまざまな分野からの例の分析.
  • 視聴者の算数能力とインタラクティブビジュアライゼーションの可能性を考慮する.

主要な成果:

  • 不確実性の視覚的な伝達は一般的だが,強固な経験的根拠がない.
  • ビジュアライゼーションの有効性は,視聴者の算数能力とグラフィックデザインの影響を受けます.
  • インタラクティブで適応可能なビジュアライゼーションは,カスタマイズされたコミュニケーションの約束を示しています.

結論:

  • 不確実性を視覚的に伝えるには,聴衆と文脈を慎重に考慮する必要があります.
  • インタラクティブなビジュアライゼーションは理解を深めることができますが,すべてのコミュニケーションの課題を解決することはありません.
  • 不完全または論争の的知識からのより深い不確実性に対処することは,依然としてオープンな研究分野です.