Related Experiment Video
Updated: Aug 24, 2026

09:13
Testing Sensory and Multisensory Function in Children with Autism Spectrum Disorder
Published on: April 22, 2015
Do signers think differently? The processing of number parity in deaf participants
Wiebke Iversen1, Hans-Christoph Nuerk, Klaus Willmes
1University of Cologne, Technical University Aachen: Collaborative Research Centre Media and Cultural Commmunication. wiebke.iversen@uni-koeln.de
Abstract
No abstract available in PubMed .
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Sign Test for Matched Pairs
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in value between...
To conduct the sign test, we first calculate the differences in value between...
Parallel Processing
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
Introduction to the Sign Test
The sign test is an important tool in nonparametric statistics, offering a straightforward yet effective method for analyzing matched pairs, nominal data, or hypotheses concerning the median of a population. It transforms data points into positive or negative signs, avoiding the need for assumptions about data distribution and instead focusing on the direction of change. It is particularly valuable when data does not conform to the normal distribution requirements of many parametric tests. For...