Related Experiment Video

Updated: Aug 15, 2026

Assessing Dyslexia at Six Year of Age
15:00

Assessing Dyslexia at Six Year of Age

Published on: May 1, 2020

Diagnostic closure and the spread of uncertainty

M H Cohen

    Issues in Comprehensive Pediatric Nursing
    |July 1, 1993
    PubMed

    More Related Videos

    Enhanced Communication of Tumor Margins Using 3D Scanning and Mapping07:47

    Enhanced Communication of Tumor Margins Using 3D Scanning and Mapping

    Published on: December 15, 2023

    Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease06:16

    Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

    Published on: August 9, 2024

    Related Concept Videos

    Decision Making: Traditional Method01:14

    Decision Making: Traditional Method

    The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
    First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
    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.
    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...
    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...
    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...
    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...