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Wald-Wolfowitz Runs Test I01:17

Wald-Wolfowitz Runs Test I

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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...
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Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

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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.
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Surveys

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Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
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Segregation in Fresh Concrete01:16

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Segregation in fresh concrete is a phenomenon where the components of the concrete mix separate, leading to uneven distribution and compromised structural integrity. This separation typically occurs when concrete is subjected to excessive horizontal movement within forms, or when it is dropped from considerable heights or forced through narrow, winding paths. As a result, heavier coarse aggregate particles settle at the bottom, while lighter, finer materials such as cement and water rise to the...
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Stratified Sampling Method01:16

Stratified Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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Sampling Plans

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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
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Related Experiment Video

Updated: Aug 26, 2025

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations
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Monitoring Spatial Segregation in Surface Colonizing Microbial Populations

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Quantifying ethnic segregation in cities through random walks.

Sandro Sousa1,2, Vincenzo Nicosia3

  • 1School of Mathematical Sciences, Queen Mary University of London, London, UK. ssou@itu.dk.

Nature Communications
|October 3, 2022
PubMed
Summary
This summary is machine-generated.

We introduce new non-parametric measures for spatial segregation using random walks on graphs. These methods consistently estimate segregation and allow for cross-system comparisons, revealing links to socioeconomic deprivation.

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Area of Science:

  • Urban studies
  • Spatial analysis
  • Network science

Background:

  • Socioeconomic segregation significantly contributes to urban inequalities.
  • Existing spatial segregation measures have limitations in scale dependency, neglecting spatial correlations, and relying on ad-hoc parameters, hindering cross-system comparisons.

Purpose of the Study:

  • To propose a novel family of non-parametric measures for spatial distributions.
  • To enable consistent and comparable estimations of segregation across diverse urban systems.
  • To analyze ethnic segregation in US and UK metropolitan areas and its association with socioeconomic factors.

Main Methods:

  • Utilizing the statistics of random walk trajectories on graphs representing spatial systems.
  • Developing non-parametric measures based on diffusion on graphs to quantify spatial diversity.
  • Applying these measures to analyze ethnic segregation patterns in metropolitan areas.

Main Results:

  • The proposed measures provide consistent estimations of segregation in synthetic and real spatial patterns.
  • Ethnic segregation in US and UK metropolitan areas was analyzed using graph diffusion.
  • Spatial diversity measures showed strong associations with socioeconomic deprivation.

Conclusions:

  • The novel graph-based diffusion measures offer a robust and comparable method for assessing spatial segregation.
  • These measures overcome limitations of traditional methods, allowing for analysis across urban areas of varying characteristics.
  • The findings highlight a significant link between ethnic segregation, spatial diversity, and socioeconomic deprivation in urban environments.