IBM SPSS Statistics (or more commonly, SPSS) is known to the public as one of the most widely used statistical analysis packages, with practical usage in multiple fields. Providing advanced data management tools, it provides a comprehensive set of utilities that work together in order to analyze large data sets, detect trends and generate accurate predictions.

The suite is mainly intended for analysts and statistical programmers who have advanced knowledge on statistical methods and research tools and their usage in making better decisions. However, the standard edition comprises basic statistical and graphics capabilities, suitable for the regular user. The data editor included in the package is similar to any spreadsheet application, enabling you to manually enter data or import a database from Cognos BI, Excel, Lotus, dBase, text or tab-delimited files.

Along with the data management tools that help you process large data sets (data validation, duplicate identification, data comparison, variable sorting, file merging, splitting and restructuring etc.), the application comes with advanced statistical analysis features. It supports descriptive statistics (calculating frequencies, ratios and generating plots), specific tests (T tests, ANOVA etc.), linear and generalized model processing, correlation determining, regression and curve estimations, neural networking, data classification (two-step, K-Means and hierarchical cluster), reliability analysis and more.

Additionally, it allows trend forecasting, enabling you to create models and run spectral analysis and features quality control, ROC curve analysis, and data simulation capabilities. As expected, it bundles a variate collection of graph templates and a variable editor. The package also includes an output viewer especially designed for data visualization, as well as a script editor for task automation purposes.

To sum up, IBM SPSS Statistics is dedicated to meet the requirements of professional researchers and analysts. With support for advanced statistical procedures, it enables you to generate an insight of a complex data set, predicts trends and easily creates time-series forecasts.