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README.md
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tags:
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- evaluate
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- metric
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---
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# Metric Card for Spearman Correlation Coefficient Metric (spearmanr)
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tags:
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- evaluate
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- metric
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description: >-
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The Spearman rank-order correlation coefficient is a measure of the
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relationship between two datasets. Like other correlation coefficients,
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this one varies between -1 and +1 with 0 implying no correlation.
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Positive correlations imply that as data in dataset x increases, so
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does data in dataset y. Negative correlations imply that as x increases,
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y decreases. Correlations of -1 or +1 imply an exact monotonic relationship.
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Unlike the Pearson correlation, the Spearman correlation does not
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assume that both datasets are normally distributed.
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The p-value roughly indicates the probability of an uncorrelated system
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producing datasets that have a Spearman correlation at least as extreme
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as the one computed from these datasets. The p-values are not entirely
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reliable but are probably reasonable for datasets larger than 500 or so.
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---
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# Metric Card for Spearman Correlation Coefficient Metric (spearmanr)
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