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

Wald-Wolfowitz Runs Test I01:17

Wald-Wolfowitz Runs Test I

The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...
Characteristics of OpAmp01:17

Characteristics of OpAmp

The operational amplifier, commonly known as an op-amp, is a specially designed electronic circuit component. Its purpose is to work in conjunction with other circuit elements to execute a defined signal-processing operation. Consider an equivalent circuit model of an op-amp, as depicted in Figure 1; the output section comprises a voltage-controlled source in parallel with the output resistance Ro.
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first column of the Routh...
Plotting and Calibrating the Root Locus01:19

Plotting and Calibrating the Root Locus

Root loci often diverge as system poles shift from the real axis to the complex plane. Key points in this transition are the breakaway and break-in points, indicating where the root locus leaves and reenters the real axis. The branches of the root locus form an angle of 180/n degrees with the real axis, where n is the number of branches at a breakaway or break-in point.
The maximum gain occurs at the breakaway points between open-loop poles on the real axis, while the minimum gain is observed...
Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...

You might also read

Related Articles

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

Sort by
Same author

Alternative urban drinking water supply scenarios under climate change: evaluation of carbon footprint and energy demands.

Journal of environmental health science & engineering·2026
Same author

Hydrogeochemical assessment and health risks of groundwater in sahand volcanic foreland (NW Iran): Arsenic speciation and heavy metal risk indicators.

Ecotoxicology and environmental safety·2026
Same author

Application of multi-criteria group decision-making for water quality management.

Environmental monitoring and assessment·2024
Same author

Circular Lotka-Volterra Competitive System with Discrete Time Delays.

Nonlinear dynamics, psychology, and life sciences·2024
Same author

Developing sustainable land-use patterns at watershed scale using nexus of soil, water, energy, and food.

The Science of the total environment·2022
Same author

Delay Cournot duopoly models revisited.

Chaos (Woodbury, N.Y.)·2018

Related Experiment Video

Updated: Jul 6, 2026

Data Acquisition Protocol for Determining Embedded Sensitivity Functions
07:46

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

Sensitivity analysis of the OWA operator.

Mahdi Zarghami1, Ferenc Szidarovszky, Reza Ardakanian

  • 1Systems and Industrial Engineering Department, University of Arizona, Tucson, AZ 85721, USA.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|March 20, 2008
PubMed
Summary
This summary is machine-generated.

This study compares two methods for calculating order weights in the ordered weighted averaging (OWA) decision-making tool. The minimal variability method offers better computational efficiency due to its linear behavior.

Failed At:

2026-06-19T13:36:09.131435+00:00

More Related Videos

Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station
05:57

Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station

Published on: April 1, 2020

A Guide to Concentration Alternating Frequency Response Analysis of Fuel Cells
11:18

A Guide to Concentration Alternating Frequency Response Analysis of Fuel Cells

Published on: December 11, 2019

Related Experiment Videos

Last Updated: Jul 6, 2026

Data Acquisition Protocol for Determining Embedded Sensitivity Functions
07:46

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station
05:57

Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station

Published on: April 1, 2020

A Guide to Concentration Alternating Frequency Response Analysis of Fuel Cells
11:18

A Guide to Concentration Alternating Frequency Response Analysis of Fuel Cells

Published on: December 11, 2019