scipy.stats.probplot(x, sparams=(), dist='norm', fit=1, plot=None)

Return (osm, osr){,(scale,loc,r)} where (osm, osr) are order statistic medians and ordered response data respectively so that plot(osm, osr) is a probability plot. If fit==1, then do a regression fit and compute the slope (scale), intercept (loc), and correlation coefficient (r), of the best straight line through the points. If fit==0, only (osm, osr) is returned.

sparams is a tuple of shape parameter arguments for the distribution.

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