Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

47.1K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
47.1K
McNemar's Test01:23

McNemar's Test

938
McNemar's Test is a nonparametric statistical test used to determine if there is a significant difference in proportions between two related groups when the outcome is binary (e.g., yes/no, success/failure). It is beneficial when we have paired data, such as pre-test/post-test designs, where the same subjects are measured under two different conditions. The test is named after the statistician Quinn McNemar, who introduced it in 1947. It is commonly used in situations where subjects are...
938
Stereotypes, Prejudice, and Discrimination02:55

Stereotypes, Prejudice, and Discrimination

95.9K
Humans are very diverse and although we share many similarities, we also have many differences. The social groups we belong to help form our identities (Tajfel, 1974). These differences may be difficult for some people to reconcile, which may lead to prejudice toward people who are different. Prejudice is a negative attitude and feeling toward an individual based solely on one’s membership in a particular social group (Allport, 1954; Brown, 2010). Prejudice is common against people who...
95.9K
How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

40.0K
Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
40.0K
Nominal Level of Measurement00:56

Nominal Level of Measurement

41.0K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. Not every statistical operation can be used with every set of data. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
The data that cannot be measured but can be grouped into categories fall under the nominal level of measurement. Data that is measured using a nominal...
41.0K
Test for Homogeneity01:23

Test for Homogeneity

2.5K
The goodness–of–fit test can be used to decide whether a population fits a given distribution, but it will not suffice to decide whether two populations follow the same unknown distribution. A different test, called the test for homogeneity, can be used to conclude whether two populations have the same distribution. To calculate the test statistic for a test for homogeneity, follow the same procedure as with the test of independence. The hypotheses for the test for homogeneity can...
2.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Using posterior probability informed thresholds to develop best practice recommendations for MorphoPASSE using the innominate, cranial, and combined traits.

Journal of forensic sciences·2025
Same author

Reevaluating skeletal sex estimation practices in forensic anthropology.

Journal of forensic sciences·2025
Same author

Sex estimation using metrics of the innominate: A test of the DSP2 method.

Journal of forensic sciences·2024
Same author

Characterization of the Entner-Doudoroff pathway in <i>Pseudomonas aeruginosa</i> catheter-associated urinary tract infections.

Journal of bacteriology·2023
Same author

Characterization of the Entner-Douderoff Pathway in <i>Pseudomonas aeruginosa</i> Catheter-associated Urinary Tract Infections.

bioRxiv : the preprint server for biology·2023
Same author

Commentary on: Bethard JD, DiGangi EA. Letter to the Editor-Moving beyond a lost cause: Forensic anthropology and ancestry estimates in the United States. J Forensic Sci. 2020;65(5):1791-2. doi: 10.1111/1556-4029.14513.

Journal of forensic sciences·2020

Related Experiment Video

Updated: Mar 9, 2026

A Modified Trier Social Stress Test for Vulnerable Mexican American Adolescents
06:15

A Modified Trier Social Stress Test for Vulnerable Mexican American Adolescents

Published on: July 10, 2017

13.9K

Improving Nonmetric Sex Classification for Hispanic Individuals.

Alexandra R Klales1, Stephanie J Cole2

  • 1Sociology & Anthropology, Washburn University, 1700 SW College Ave, Topeka, KS, 66621.

Journal of Forensic Sciences
|January 11, 2017
PubMed
Summary

Forensic anthropology methods for sex estimation perform poorly on Hispanic individuals. This study recalibrates existing methods, improving accuracy and reducing bias for more reliable identification of Hispanic skeletal remains.

Keywords:
Hispanicsborder crossersforensic anthropologyforensic sciencenonmetric traitspelvissex estimationskull

More Related Videos

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
08:13

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

6.9K
Sexual Transmission of American Trypanosomes from Males and Females to Naive Mates
13:55

Sexual Transmission of American Trypanosomes from Males and Females to Naive Mates

Published on: January 27, 2019

15.7K

Related Experiment Videos

Last Updated: Mar 9, 2026

A Modified Trier Social Stress Test for Vulnerable Mexican American Adolescents
06:15

A Modified Trier Social Stress Test for Vulnerable Mexican American Adolescents

Published on: July 10, 2017

13.9K
Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
08:13

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

6.9K
Sexual Transmission of American Trypanosomes from Males and Females to Naive Mates
13:55

Sexual Transmission of American Trypanosomes from Males and Females to Naive Mates

Published on: January 27, 2019

15.7K

Area of Science:

  • Forensic Anthropology
  • Biological Anthropology
  • Human Osteology

Background:

  • Current forensic anthropology methods for skeletal identification are primarily based on U.S. Black and White populations.
  • These methods exhibit poor performance and high misclassification rates when applied to Hispanic individuals.
  • There is a critical need for population-specific standards for Hispanic identification.

Purpose of the Study:

  • To evaluate the classification accuracies of existing nonmetric sex estimation methods (Walker 2008, Klales et al. 2012).
  • To recalibrate these methods using a sample of modern Hispanic individuals.
  • To develop population-specific regression equations for improved sex estimation in Hispanics.

Main Methods:

  • Collected ordinal data for five cranial and three pelvic nonmetric traits from 54 modern Hispanic individuals.
  • Applied original Walker and Klales et al. methods to the Hispanic sample.
  • Recalibrated regression equations for both methods using the collected Hispanic data.

Main Results:

  • Recalibration of the Klales et al. method increased classification accuracy from 90.3% to 94.1%.
  • Recalibration of the Walker method decreased accuracy from 81.5% to 74.1% but significantly improved sex bias from 22.2% to -7.4%.
  • The recalibrated equations demonstrate enhanced appropriateness for sex estimation in Hispanic populations.

Conclusions:

  • Recalibrated methods provide more accurate and less biased sex estimation for Hispanic skeletal remains.
  • Population-specific standards are essential for reliable forensic anthropological identification.
  • These findings contribute to improving the accuracy of forensic identification for diverse populations.