The nonlinear axis class is taken from one of the matplotlib examples. Return max(vmin, 1e-6), min(vmax, 1-1e-6)Ĭlass PPFTransform(mtransforms.Transform):Ĭlass IPPFTransform(mtransforms.Transform): In the Graph variables cell, enter the column that contains the raw data. Probability plots might be the best way to determine whether your data follow a. Return np.array()/100.0Īxis.set_major_formatter(PercFormatter())Īxis.set_minor_formatter(PercFormatter())ĭef limit_range_for_scale(self, vmin, vmax, minpos): Im using Minitab, which can test 14 probability distributions and two. Here is the code for the base plot and the fit: import numpy as npįrom matplotlib import transforms as mtransformsįrom matplotlib.ticker import Formatter, Locatorĭef set_default_locators_and_formatters(self, axis): I recently fielded an interesting question about the probability and survival plots in Minitab Statistical Software's Reliability/Survival menus. None of the definitions I found yields something similar. I have an answer for the first part of the task but I am not sure how minitab calculates the confidence interval.
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