SPSS 17.0.1 Portable with all modules ( 187 MB )
Latest version Just extract and use!
Statistics included in the base software:
* Descriptive statistics: Cross tabulation, Frequencies,Descriptives, Explore, Descriptive Ratio Statistics
* Bivariate statistics: Means, ttest, ANOVA, Correlation (bivariate, partial, distances), Nonparametric tests
* Prediction for numericaloutcomes: Linear regression
* Prediction for identifying groups: Factor analysis, cluster analysis (twostep, Kmeans, hierarchical), Discriminant
The many features of SPSS are accessible viapulldown menus or can be programmed with a proprietary 4GL command syntax language. Command syntax programming has the benefits of reproducibility; simplifying repetitive tasks; and handlingcomplex data manipulations and analyses. The pulldown menu interface also generates command syntax, though the default settings have to be changed to make the syntax visible to the user. Programscan 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 Pythonprogrammability 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 statisticsin the free software package R. From version 14 onwards SPSS can be driven externally by a Python or a VB.NET program using supplied "plugins".
SPSS places constraints on internalfile structure, data types, data processing and matching files, which together considerably simplify programming. SPSS datasets have a 2dimensional table structure where the rows typicallyrepresent 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 casebycase through the file. Files can be matched onetoone and onetomany, but not manytomany.
The graphical user interface hastwo 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). Unlikespreadsheets, 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 variableand 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 filestructure 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 computerassisted 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 andwrite 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 inpackageviewer, a standalone 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,tabdelimited text, PDF, XLS, HTML, XML, SPSS dataset or a variety of graphic image formats (JPEG, PNG, BMP and EMF).
Addon 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 reportingof suspicious values.
* SPSS Regression Models Logistic regression, ordinal regression, multinomial logistic regression, and mixed models.
* SPSS Advanced Models Multivariate GLM andrepeated 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 userdefined 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 regressionbased imputation.
* SPSS Map
* SPSS Complex Samples (added in Version 12). Adjusts for stratification and clustering and other sample selectionbiases.

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