The cumulative failure probability, Pf, was calculated by first sorting the data by the effective diameter at failure, d, from smallest to largest. Then, each data point was assigned an index, i = 1,2,3…. The cumulative probability was calculated using the following equation: Pf = (i-0.5)/n, where n is the number of samples . The standard deviation of the fitted parameters was calculated using the bootstrapping scheme . Briefly, the original dataset was sampled with replacement, generating a new synthetic dataset with the same number of datapoints as the original. Then, the fitting procedure was performed, and the parameters were computed. This process was repeated 1,000 times to generate a range of fitting parameters, from which the standard deviation was computed. Fitting was performed using least-squares linear regression using the statsmodels package in conjunction with Pandas and numpy packages in Python 3.8.