Statistics - Distribution Fitting

Ribbon bar. Select the Statistics tab. In the Base group, click Distribution Fitting to display the Distribution Fitting Startup Panel.

Classic menus. On the Statistics menu, select Distribution Fitting to display the Distribution Fitting Startup Panel.

The Distribution Fitting module is used to fit a variety of continuous and discrete distributions to the data.

The fit can be evaluated via the Chi-square test or the Kolmogorov-Smirnov one-sample test (the fitting parameters can be controlled); the Lilliefors and Shapiro-Wilk tests are also supported. In addition, the fit of a particular hypothesized distribution to the empirical distribution can be evaluated in customized histograms (standard or cumulative) with overlaid selected functions; line and bar graphs of expected and observed frequencies, discrepancies and other results can be produced from the output spreadsheets.

Other distribution fitting options are available in STATISTICA Process Analysis, where you can compute maximum-likelihood parameter estimates for the Beta, Exponential, Extreme Value (Type I, Gumbel), Gamma, Log-Normal, Rayleigh, and Weibull distributions. Also included in that module are options for automatically selecting and fitting the best distribution for the data, as well as options for general distribution fitting by moments (via Johnson and Pearson curves). User-defined 2- and 3-dimensional functions can also be plotted and overlaid on the graphs. The functions can reference a wide variety of distributions such as the Beta, Binomial, Cauchy, Chi-square, Exponential, Extreme value, F, Gamma, Geometric, Laplace, Logistic, Normal, Log-Normal, Pareto, Poisson, Rayleigh, t (Student), or Weibull distribution, as well as their integrals and inverses.