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In addition to computing Pearson's correlation, the Scipy function produces a two-tailed p-value, which provides some indication of the likelihood that two totally uncorrelated objects might produce a Pearson's correlation value as extreme as the calculated value See Glossary item, p-value.
If we were comparing two sets of data and found a Pearson correlation of zero, then we might assume that the two sets of data were uncorrelated, and that it would be futile to try to model i.
One method to calculate the correlation of a numerical variable with a categorical one is to convert the numerical variable into categories.
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Moreover, the strict equality of variances is not required for convergence of reliability estimates across methods.
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