Related Experiment Video

Updated: Aug 22, 2026

Assessment of Child Anthropometry in a Large Epidemiologic Study
09:36

Assessment of Child Anthropometry in a Large Epidemiologic Study

Published on: February 2, 2017

Measures of excellence: the search for the gold standard

V H Holtz

    Bulletin of the Medical Library Association
    |October 1, 1986
    PubMed

    More Related Videos

    Using Gold-standard Gait Analysis Methods to Assess Experience Effects on Lower-limb Mechanics During Moderate High-heeled Jogging and Running06:35

    Using Gold-standard Gait Analysis Methods to Assess Experience Effects on Lower-limb Mechanics During Moderate High-heeled Jogging and Running

    Published on: September 14, 2017

    Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning10:39

    Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

    Published on: August 29, 2025

    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.
    Testing a Claim about Standard Deviation01:19

    Testing a Claim about Standard Deviation

    A complete procedure to test a claim about population standard deviation or population variance is explained here.
    The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
    As a first step, the hypothesis (null and alternative) concerning the claim about...
    Detection of Gross Error: The Q Test01:00

    Detection of Gross Error: The Q Test

    When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
    Quantifying and Rejecting Outliers: The Grubbs Test01:02

    Quantifying and Rejecting Outliers: The Grubbs Test

    Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This number is...
    Quality Control01:05

    Quality Control

    Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results.
    Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
    Measures of Intelligence01:29

    Measures of Intelligence

    Psychologists measure intelligence by using standardized tests that produce a score known as the intelligence quotient or IQ. To understand IQ tests, it's important to recognize the key principles behind their construction: validity, reliability, and standardization.
    Validity refers to how well a test measures what it claims to measure. An intelligence test should accurately assess intelligence rather than another characteristic, like anxiety. Criterion validity is one way to evaluate this; it...