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Related Concept Videos

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.
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The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under...
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A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
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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...
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An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a  sample proportion. However, unlike the point estimate which is a single value, the confidence interval  contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
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Effects of feedback01:24

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Feedback in control systems plays a critical role in shaping various operational parameters, extending beyond simple error reduction to influence stability, bandwidth, gain, impedance, and sensitivity. Understanding these effects requires examining a basic feedback system characterized by defined input, output, error, and feedback signals.
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Related Experiment Video

Updated: Jul 11, 2025

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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More specific feedback: why "confidence" in feedback is too ambiguous.

Maxwell Uetz1, Sonia Ananthakrishnan2, Asher Tulsky3

  • 1Internal Medicine Residency Program, Department of Medicine, Boston Medical Center, 72 East Concord Street, Boston, MA 02118.

Postgraduate Medical Journal
|November 16, 2023
PubMed
Summary
This summary is machine-generated.

Feedback in medical education should be actionable and specific, not based on "confidence." This subjective feedback risks bias and emotional harm, prompting a call for its moratorium. Educators should focus on observable behaviors instead.

Keywords:
general medicineinternal medicinemedical education & training

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Area of Science:

  • Medical Education
  • Healthcare Professional Development
  • Clinical Skills Assessment

Background:

  • High-quality feedback is crucial for trainee development.
  • Current feedback practices may include subjective elements like "confidence."
  • The impact of "confidence"-based feedback on learning and potential biases is not well understood.

Purpose of the Study:

  • To evaluate the utility and potential harms of using "confidence" in medical education feedback.
  • To advocate for a shift towards more objective and actionable feedback methods.
  • To propose a moratorium on "confidence"-based feedback pending further research.

Main Methods:

  • Qualitative analysis of feedback principles.
  • Discussion of potential biases (gender, cultural) in subjective feedback.
  • Review of existing literature on feedback in medical training.

Main Results:

  • "Confidence" lacks specificity and actionable steps for improvement.
  • "Confidence"-based feedback risks subjective judgments and potential bias.
  • Emotional harm to trainees is a concern with this feedback type.

Conclusions:

  • "Confidence" is an inappropriate metric for feedback in medical education.
  • A moratorium on "confidence"-based feedback is recommended.
  • Focus should shift to specific, observable, and behavioral feedback for effective learning.