Statistics Base
What's new
The analytical capabilities added to SPSS 15.0 will boost important predictive applications such as fraud detection and fast-track claims settlements, customer feedback management and call center management.
Key Enhancements of SPSS 15.0:
Better reporting
- Extending the Chart Builder, a highly visual chart creation interface that was added in SPSS 14.0. Chart Builder enables customers to attain enhanced chart creation performance and more robust features for popular chart types such as scatterplot matrices, histograms and population pyramids.
- New chart types -- dual-Y axis and overlay charts -- allowing customers to reveal more complex information and allow for more sophisticated reporting.
- Easily export SPSS reports to PDF. Several options are available to enable the exporting of PDF documents.
More powerful data management
- Allowing enterprises to seamlessly work with data in SPSS and Dimensions products now that you can both import and export the Dimensions Data Model.
- Easily writing back to databases from SPSS by using the Export to Database Wizard.
- Enabling customers to use their own dictionary information for variables with Custom Attributes. For example, document transformations for a derived variable with information explaining how the variable was transformed.
- Work more easily with very wide data files by customising variable sets. Instantly reduce the variable view to a subset of selected variables, while keeping the entire file loaded and available for analysis.
- More accurately use algorithms designed for nominal attributes (such as Naive Bayes and logit models) with Optimal Binning in the SPSS Data Preparation add-on module. Optimal Binning will preprocess data to set cutpoints for scale variables to help customers reach the best possible outcome.
More powerful statistics
- Address a wide range of statistical modeling problems using generalised linear models (GZLMs) and generalised estimating equations (GEEs) in the SPSS Advanced Models add-on module. GZLMs and GEEs represent a unifying framework that includes classical linear models with normally distributed dependent variable, logistic and probit models for binary data; and loglinear models for count data, as well as various other nonstandard regression-type models. GEE extends the GZLM framework by allowing customers to fit a variety of longitudinal models.
- Accurately predict ordinal outcomes from a complex sample design by using complex samples ordinal regression in the SPSS Complex Samples add-on module.
- Gain expanded statistical options based on Bayesian estimation for ordered categorical and censored data with Amos 7.0 structural equation modeling (SEM) software.
More powerful programmability
- The SPSS Programmability Extension, introduced in SPSS Base 14.0, allowing users to extend the SPSS command syntax language with the full capabilities of a chosen external programming language such as Python or Visual Basic. The external language can be used to build jobs that respond to datasets, output and environment, contain more automation, are more robust and are more maintainable.
- New features in SPSS 15.0 for users of the SPSS Programmability Extension are:
- Ability to create procedures in external languages and build them into SPSS, complete with a user interface and the results delivered to an interactive SPSS pivot table in the Output Viewer.
- Read and write case data
- Create new variables directly
Support for the Predictive Enterprise
- For enterprise customers, SPSS 15.0 includes powerful new capabilities that enable customers to share data assets enterprisewide. In particular, the SPSS Adapter for SPSS Predictive Enterprise Services provides a centralised, secure, auditable repository for analytical assets and processes. With the SPSS Adapter, SPSS 15.0 integrates into the SPSS Predictive Enterprise Services platform. With SPSS Predictive Enterprise Services, enterprises can:
- Safeguard the value of analytics with version control, access control and other security features
- Ensure compliance with regulatory requirements by using a centralised, auditable repository
- Improve the productivity of analysts by providing users consistent, current files
- Through centralisation, minimise the IT costs of managing analytics