SPSS

PASW

Developer(s)	SPSS Inc.
Initial release	1968
Stable release	18.0 (Win / Mac / Linux) / 2009
Operating system	Windows, Linux / UNIX & Mac
Platform	Java
Type	Statistical analysis
License	Proprietary software
Website	www.spss.com

PASW (formerly SPSS) is a computer program used for statistical analysis. Before 2009 it was called SPSS, but in 2009 it was re-branded as PASW (Predictive Analytics SoftWare).^[1] The company announced July 28, 2009 that it was being acquired by IBM for US$1.2 billion.^[2]

Statistics program

SPSS (originally, Statistical Package for the Social Sciences) was released in its first version in 1968 after being developed by Norman H. Nie and C. Hadlai Hull. Norman Nie was then a political science postgraduate at Stanford University, and now Research Professor in the Department of Political Science at Stanford and Professor Emeritus of Political Science at the University of Chicago.^[3] SPSS is among the most widely used programs for statistical analysis in social science. It is used by market researchers, health researchers, survey companies, government, education researchers, marketing organizations and others. The original SPSS manual (Nie, Bent & Hull, 1970) has been described as 'Sociology's most influential book'.^[4] In addition to statistical analysis, data management (case selection, file reshaping, creating derived data) and data documentation (a metadata dictionary is stored in the datafile) are features of the base software.

Statistics included in the base software:

• Descriptive statistics: Cross tabulation, Frequencies, Descriptives, Explore, Descriptive Ratio Statistics
• Bivariate statistics: Means, t-test, ANOVA, Correlation (bivariate, partial, distances), Nonparametric tests
• Prediction for numerical outcomes: Linear regression
• Prediction for identifying groups: Factor analysis, cluster analysis (two-step, K-means, hierarchical), Discriminant

The many features of SPSS are accessible via pull-down menus or can be programmed with a proprietary 4GL command syntax language. Command syntax programming has the benefits of reproducibility; simplifying repetitive tasks; and handling complex data manipulations and analyses. Additionally, some complex applications can only be programmed in syntax and is not accessible through the menu structure. The pull-down menu interface also generates command syntax, this can be displayed in the output though the default settings have to be changed to make the syntax visible to the user; or can be paste into a syntax file using the "paste" button present in each menu. Programs can be run interactively, or unattended using the supplied Production Job Facility. Additionally a "macro" language can be used to write command language subroutines and a Python programmability extension can access the information in the data dictionary and data and dynamically build command syntax programs. The Python programmability extension, introduced in SPSS 14, replaced the less functional SAX Basic "scripts" for most purposes, although SaxBasic remains available. In addition, the Python extension allows SPSS to run any of the statistics in the free software package R. From version 14 onwards SPSS can be driven externally by a Python or a VB.NET program using supplied "plug-ins".

SPSS places constraints on internal file structure, data types, data processing and matching files, which together considerably simplify programming. SPSS datasets have a 2-dimensional table structure where the rows typically represent cases (such as individuals or households) and the columns represent measurements (such as age, sex or household income). Only 2 data types are defined: numeric and text (or "string"). All data processing occurs sequentially case-by-case through the file. Files can be matched one-to-one and one-to-many, but not many-to-many.

The graphical user interface has two views which can be toggled by clicking on one of the two tabs in the bottom left of the SPSS window. The 'Data View' shows a spreadsheet view of the cases (rows) and variables (columns). Unlike spreadsheets, the data cells can only contain numbers or text and formulas cannot be stored in these cells. The 'Variable View' displays the metadata dictionary where each row represents a variable and shows the variable name, variable label, value label(s), print width, measurement type and a variety of other characteristics. Cells in both views can be manually edited, defining the file structure and allowing data entry without using command syntax. This may be sufficient for small datasets. Larger datasets such as statistical surveys are more often created in data entry software, or entered during computer-assisted personal interviewing, by scanning and using optical character recognition and optical mark recognition software, or by direct capture from online questionnaires. These datasets are then read into SPSS.

SPSS can read and write data from ASCII text files (including hierarchical files), other statistics packages, spreadsheets and databases. SPSS can read and write to external relational database tables via ODBC and SQL.

Statistical output is to a proprietary file format (*.spv file, supporting pivot tables) for which, in addition to the in-package viewer, a stand-alone reader can be downloaded. The proprietary output can be exported to text or Microsoft Word. Alternatively, output can be captured as data (using the OMS command), as text, tab-delimited text, PDF, XLS, HTML, XML, SPSS dataset or a variety of graphic image formats (JPEG, PNG, BMP and EMF).

Add-on modules provide additional capabilities. The available modules are:

• SPSS Programmability Extension (added in version 14). Allows Python programming control of SPSS.
• SPSS Data Validation (added in version 14). Allows programming of logical checks and reporting of suspicious values.
• SPSS Regression Models - Logistic regression, ordinal regression, multinomial logistic regression, and mixed models.
• SPSS Advanced Models - Multivariate GLM and repeated measures ANOVA (removed from base system in version 14).
• SPSS Classification Trees. Creates classification and decision trees for identifying groups and predicting behaviour.
• SPSS Tables. Allows user-defined control of output for reports.
• SPSS Exact Tests. Allows statistical testing on small samples.
• SPSS Categories
• SPSS Trends
• SPSS Conjoint
• SPSS Missing Value Analysis. Simple regression-based imputation.
• SPSS Map
• SPSS Complex Samples (added in Version 12). Adjusts for stratification and clustering and other sample selection biases.

SPSS Server is a version of SPSS with a client/server architecture. It has some features not available in the desktop version, such as scoring functions.

Versions

Early versions of SPSS were designed for batch processing on mainframes, including for example IBM and ICL versions, originally using punched cards for input. A processing run read a command file of SPSS commands and either a raw input file of fixed format data with a single record type, or a 'getfile' of data saved by a previous run. To save precious computer time an 'edit' run could be done to check command syntax without analysing the data. From version 10 (SPSS-X) in 1983, data files could contain multiple record types.

SPSS version 16.0 runs under Windows, Mac OS 10.5 and earlier, and Linux. The graphical user interface is written in Java. The Mac OS version is provided as a Universal binary, making it fully compatible with both PowerPC and Intel-based Mac hardware.

Prior to SPSS 16.0, different versions of SPSS were available for Windows, Mac OS X and Unix. The Windows version was updated more frequently, and had more features, than the versions for other operating systems.

SPSS version 13.0 for Mac OS X was not compatible with Intel-based Macintosh computers, due to the Rosetta emulation software causing errors in calculations. SPSS 15.0 for Windows needed a downloadable hotfix to be installed in order to be compatible with Windows Vista.

Release history

• SPSS 15.0.1 - November 2006
• SPSS 16.0.2 - April 2008
• SPSS Statistics 17.0.1 - December 2008
• PASW Statistics 17.0.2 - March 2009
• PASW Statistics 18.0 - August 2009

See also

Wikiversity has learning materials about SPSS

• List of statistical packages
• Comparison of statistical packages
• PSPP -- an open source alternative to SPSS
• gretl - an open source alternative to SPSS that can import SPSS data files
• Rcmdr - an open source R-alternative to SPSS

Notes

References

• Levesque, R. SPSS Programming and Data Management: A Guide for SPSS and SAS Users, Fourth Edition (2007), SPSS Inc., Chicago Ill. PDF ISBN 1568273908
• SPSS 15.0 Command Syntax Reference 2006, SPSS Inc., Chicago Ill.

External links

• SPSS Inc Homepage - support page includes a searchable database of solutions
• Raynald Levesque's SPSS Tools - library of worked solutions for SPSS programmers (FAQ, command syntax; macros; scripts; python)
• Archives of SPSSX-L Discussion - SPSS Listserv active since 1996. Discusses programming, statistics and analysis
• UCLA ATS Resources to help you learn SPSS - Resources for learning SPSS
• UCLA ATS Technical Reports - Report 1 compares Stata, SAS and SPSS against R (R is a language and environment for statistical computing and graphics).
• Using SPSS For Data Analysis - SPSS Tutorial from Harvard
• SPSS Developer Central - Support for developers of applications using SPSS, including materials and examples of the Python programmability feature