Distribution Fitting 2. Pearson-Fisher, Kolmogorov-Smirnov, Anderson-Darling, Wilks-Shapiro, Cramer-von-Misses and Jarque-Bera statistics
The methods measuring the departure between observation and the model were reviewed. The following statistics were applied on two experimental data sets: Chi-Squared, Kolmogorov-Smirnov, Anderson-Darling, Wilks-Shapiro, and Jarque-Bera. Both investigated sets proved not to be normal distributed. The Grubbs test identified one outlier and after its removal the normality of the set of 205 chemical active compounds was accepted. The second data set proved not to have any outliers. Kolmogorov-Smirnov statistic is less affected by the existence of outliers (positive variation expressed as percentage smaller than 2). The outliers bring to Kolmogorov-Smirnov statistic errors of type II and to the Anderson-Darling statistic errors of type I.
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