Encyclopedia of Computational Neuroscience

Living Edition
| Editors: Dieter Jaeger, Ranu Jung

Significance Evaluation

  • Matthew T. HarrisonEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7320-6_404-1



Broadly speaking: assigning a numerical score to the “unusualness” of data relative to a specific theory. In this entry: computing a p-value for a statistical hypothesis test with emphasis on spike-train resampling.

Significance Evaluation

Deciding whether the patterns observed in experimental data support or challenge existing theories is a recurring theme in data analysis. Assigning a numerical score, or significance, is a central part of the decision process. Hypothesis testing is the classical statistical approach with p-values being the most common (but not the exclusive) method of communicating statistical significance. This entry is about basic statistical hypothesis testing with a focus on the connection between hypothesis testing and the so-called resampling methods that are gaining widespread popularity in the statistical analysis of neural firing patterns.

A comprehensive statistical analysis rarely...

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Division of Applied MathematicsBrown UniversityProvidenceUSA