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Related Concept Videos

Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

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.
The Anchoring-and-Adjustment Heuristic01:25

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In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the $2,000...
Accuracy and Precision01:52

Accuracy and Precision

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 measurements...
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Accuracy and Precision

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 measurements...
Uncertainty: Overview00:59

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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.
Uncertainty in Measurement: Reading Instruments02:46

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Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...

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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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Published on: August 25, 2023

Sources of imprecision in integrated value comparisons.

Giulia Mezzadri1, Michael Woodford2

  • 1Centre Borelli, École Normale Supérieure Paris-Saclay, 91190 Gif-sur-Yvette, France.

Cognition
|June 18, 2026
PubMed
Summary
This summary is machine-generated.

Decisions often involve comparing multiple attributes, not just one. This study reveals that human judgment accuracy in comparing sums depends on how numbers are paired, suggesting simultaneous, attribute-wise comparisons influence decision-making.

Keywords:
Attribute-wise comparisonsContext effectsModels of noisy decisionMulti-attribute choice

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Area of Science:

  • Cognitive psychology
  • Decision science
  • Neuroscience

Background:

  • Everyday decisions integrate multiple attributes, challenging independent evaluation assumptions in choice theories.
  • Attribute-wise comparisons between options significantly influence choices, contrary to traditional models.

Purpose of the Study:

  • Investigate the source of imprecision in attribute-wise comparisons.
  • Understand how framewise comparisons affect judgment accuracy in multi-attribute decision-making.

Main Methods:

  • Developed a number sequence comparison task to assess judgment accuracy.
  • Analyzed performance across conditions varying the pairing of numbers from sequences.
  • Fitted computational models (nonlinear integration, value-dependent noise) to explain observed behavior.

Main Results:

  • Accuracy in sum comparison was highest when paired values were closer in magnitude.
  • Judgments relied on simultaneous framewise comparisons, not independent option processing.
  • Heterogeneity in performance was explained by a combination of distorted value encoding and value-dependent noise.

Conclusions:

  • Attribute-wise comparisons are crucial in multi-attribute decision-making, even without subjective preferences.
  • Hybrid models combining nonlinear integration and value-dependent noise best predict human choice behavior.
  • Explaining individual differences in decision-making requires models accounting for both encoding distortions and noise variability.