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On Statistical Independence in a Contingency Table

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Foundations of Data Mining and knowledge Discovery

Part of the book series: Studies in Computational Intelligence ((SCI,volume 6))

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Abstract

This paper gives a proof showing that statistical independence in a contingency table is a special type of linear independence, where the rank of a given table as a matrix is equal to 1.0. Especially, the equation obtained is corresponding to that of projective geometry, which suggests that a contingency matrix can be interpreted in a geometrical way.

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Tsau Young Lin Setsuo Ohsuga Churn-Jung Liau Xiaohua Hu Shusaku Tsumoto

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Tsumoto, S. On Statistical Independence in a Contingency Table. In: Young Lin, T., Ohsuga, S., Liau, CJ., Hu, X., Tsumoto, S. (eds) Foundations of Data Mining and knowledge Discovery. Studies in Computational Intelligence, vol 6. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11498186_8

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  • DOI: https://doi.org/10.1007/11498186_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26257-2

  • Online ISBN: 978-3-540-32408-9

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