Related Experiment Video

Updated: Aug 15, 2026

Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision
07:57

Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision

Published on: April 29, 2014

The journal "impact factor": a misnamed, misleading, misused measure

F Hecht1, B K Hecht, A A Sandberg

  • 1Hecht Associates, Jacksonville, Florida 32210-4362, USA.

Cancer Genetics and Cytogenetics
|July 17, 1998
PubMed

More Related Videos

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

High-Throughput Automated Multiplex Immunofluorescence Assays for Translational Research09:12

High-Throughput Automated Multiplex Immunofluorescence Assays for Translational Research

Published on: June 10, 2025

Related Concept Videos

Factors Affecting Illness01:18

Factors Affecting Illness

When a person's physical, emotional, intellectual, social development or spiritual functioning is compromised, this deviation from a healthy normal state is called illness. Illness creates stress that in turn harms individuals. Irritation, anger, denial, hopelessness, and fear are behavioral and emotional changes an individual experiences in the phases of illness. A variety of factors influence a person's health and well-being.
For instance, risk factors are connected to illness, disability,...
Bias01:22

Bias

Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Identifying Statistically Significant Differences: The F-Test01:14

Identifying Statistically Significant Differences: The F-Test

The F-test is used to compare two sample variances to each other or compare the sample variance to the population variance. It is used to decide whether an indeterminate error can explain the difference in their values. The underlying assumptions that allow the use of the F-test include the data set or sets are normally distributed, and the data sets are independent of each other. The test statistic F is calculated by dividing one variance by another. In other words, the square of one standard...
Types of Impact01:30

Types of Impact

Impacts can be classified in various forms, primarily under two subgroups: central impact and oblique impact. A central impact occurs when two objects collide head-on, possessing opposite velocities aligned along the line of impact. Conversely, an oblique impact occurs when two objects collide at an angle, resulting in a modification of both direction and velocity.
The coefficient of restitution is a metric for understanding the dynamics of impacts. It quantifies the ratio of relative velocity...
Impact Loading01:19

Impact Loading

Impact loading occurs when a moving object collides with a stationary structure, such as a rod with a uniform cross-sectional area fixed at one end. Under these conditions, the rod absorbs the kinetic energy from the striking object, leading to deformation and subsequent stress development. As the rod returns to its original position and reaches maximum stress, the absorbed energy, initially manifested as kinetic energy, transforms entirely into strain energy.
In cases of elastic deformation,...
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is: