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Revealing Statistical Independence of Two Experimental Data Sets: An Improvement on Spearman’s Algorithm

  • Bogdan Badea
  • Adriana Vlad
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3980)

Abstract

A high effective statistical independence test procedure derived from Spearman’s Rank Correlation Test is presented, applicable to all kind of continuous variables (normal or not, even of unknown probability law). Some relevant practical signal processing test examples as well as a Monte Carlo performance comparison with Spearman’s Rank Correlation Test capabilities are explained. Besides describing the test procedure algorithm, the paper reveals, from an engineering point of view, some significant aspects concerning the understanding (perception) of the important and not simple concepts, i.e. testing dependence versus statistical independence.

Keywords

Scatter Diagram Statistical Independence Chaotic Signal Independence Test Linear Regression Slope 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bogdan Badea
    • 1
  • Adriana Vlad
    • 1
    • 2
  1. 1.Faculty of Electronics, Telecommunications and Information TechnologyPolitehnica University of BucharestRomania
  2. 2.The Research Institute for Artificial IntelligenceRomanian Academy 

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