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Related Concept Videos

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...
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...
Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5% chance...
Accuracy, limits, and approximation01:28

Accuracy, limits, and approximation

Accuracy, limits, and approximations are common in many fields, especially in engineering calculations. These concepts are imperative for ensuring that a given value is as close as possible to its true value.
Accuracy is defined as the closeness of the measured value to the true or actual value. In engineering mechanics, repeated measurements are taken during theoretical or experimental analyses to ensure that the result is precise and accurate.
The accuracy of any solution is based on the...
Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...

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Related Experiment Video

Updated: Jul 9, 2026

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification (ADCI) and Dose Estimation
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d'plus: A program to calculate accuracy and bias measures from detection and discrimination data.

N A Macmillan1, C D Creelman

  • 1Department of Psychology, Brooklyn College of CUNY, Brooklyn, NY 11210, USA. nmacmill@broadway.gc.cuny.edu

Spatial Vision
|January 1, 1997
PubMed
Summary

The d

Area of Science:

  • Psychology
  • Cognitive Science
  • Psychophysics

Background:

  • Accurate measurement of perceptual decision-making is crucial in various fields.
  • Existing methods may not cover diverse experimental designs.
  • Signal Detection Theory (SDT) and related models offer robust frameworks.

Purpose of the Study:

  • To introduce the d'plus software for calculating key parameters in perceptual tasks.
  • To provide a versatile tool for analyzing data from multiple experimental paradigms.

Main Methods:

  • The d'plus program utilizes Signal Detection Theory, Choice Theory, and nonparametric models.
  • It is designed to process data from one-interval, two-interval, and three-interval forced-choice tasks.
  • The software also supports same-different, ABX, and oddity paradigms.

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Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification (ADCI) and Dose Estimation
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Main Results:

  • d'plus calculates accuracy (sensitivity) and response-bias parameters.
  • The program demonstrates applicability across a wide range of common experimental designs.

Conclusions:

  • d'plus offers a unified approach to analyzing perceptual data.
  • This software enhances the quantitative analysis of decision-making in various experimental contexts.