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Related Concept Videos

Random and Systematic Errors01:20

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
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Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
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Random and Systematic Errors01:20

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Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese
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How Difference Tasks Are Affected by Probability Format, Part 1: A Making Numbers Meaningful Systematic Review.

Natalie C Benda1, Brian J Zikmund-Fisher2,3,4, Mohit M Sharma5

  • 1Columbia University School of Nursing, New York, NY, USA.

MDM Policy & Practice
|February 25, 2025
PubMed
Summary

Understanding health probabilities is crucial. Presenting data using rates per 10^n and incorporating graphics significantly improves the computation of probability differences, aiding health decision-making.

Keywords:
Decision AidsEvidence SynthesisHealth LiteracyNumeracyPhysician-Patient CommunicationRisk CommunicationRisk PerceptionShared Decision MakingSystematic Reviews

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Area of Science:

  • Health communication
  • Decision science
  • Information design

Background:

  • The Making Numbers Meaningful project conducted a systematic review to guide health probability data presentation.
  • This review focuses on "difference tasks," where individuals evaluate probability variations, such as risk factor impact.

Purpose of the Study:

  • To assess the impact of data presentation formats on the communication of health probabilities.
  • To evaluate how format influences identification, recall, contrast, categorization, and computation of probability differences.

Main Methods:

  • Systematic review of experimental and quasi-experimental studies comparing quantitative health information formats.
  • Inclusion of 53 findings from 35 studies across multiple databases and hand searches.
  • Extraction of data on stimuli, cognitive tasks, and perceptual, affective, cognitive, or behavioral outcomes.

Main Results:

  • Evidence on the effect of format on most difference-level cognitive tasks was weak or insufficient.
  • Strong evidence indicates computations with differences are easier using rates per 10^n compared to percentages or "1 in X" rates.
  • Adding graphics to numerical data enhances the ease of performing difference-level computations.

Conclusions:

  • Few studies were comparable enough to generate robust evidence on probability difference evaluation.
  • Rates per 10^n and graphical enhancements are recommended for improving the computation of probability differences in health communication.