Descriptive statistics are used to summarize or describe measured values. GSS provides a range of descriptive statistics, such as mean, median, mode, geometric mean, standard deviation, variance, standard error and many more.

GSS includes a powerful module for statistical testing, which was designed to make test selection an intuitive process. In addition, it is very comprehensive, includes all standard tests and also many tests that are not often found in other statistical software. For an easy start into statistical hypothesis testing, GSS supports various ways to enter data. Hence there is no need for previous data processing or formatting. 

The intuitive user interface then provides step by step guidance through the data analyses, allowing even those with less experience to easily find the right statistical tests for the given datatype and purpose. For any remaining uncertainties a built-in statistical guide and comprehensive help is available. In short, GSS helps anyone to understand the statistical background of the tests available and on how to interpret results.

All versions of GSS include a very powerful module for dose response analysis. GSS offers a variety of mathematical functions which can be fitted to the measured data to find the best possible description of the dose response relationship. Various goodness-of-fit measures are therefore available to justify the selection of a fitted function. In addition, confidence limits and confidence bands are provided to assess the uncertainty of an estimated parameter and of the uncertainty of the dose-response relationship.

Distribution fitting is an essential part of many statistical analyses, because without knowing how your data is distributed it may be difficult to find an adequate statistical test for your data. In case you are in doubt about the distribution of the data, you can use the distribution fitting tool implemented in GSS.

Also, a curve fitting tool is included in GSS, which helps you to describe relationships or to assess correlations. In order to determine which function best describes your data, GSS calculates various goodness of fit measures. In addition, several correlations tests can be conducted, including Pearson, Spearman, Kendall’s (tau-b and tau-c) or Somer’s measure of association.

For the visualisation of your data GSS includes a powerful chart building tool, designed to produce clean graphs suitable for scientific publications. Furthermore, there are many options to customise graphs and to save your favourite chart designs for future use. The chart designer also includes a functionality for adding curve fits to your charts.