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Statistical Package for the Social Sciences (SPSS) version 16

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SPSS Statistics is a software package used for logical batched and non-batched statistical analysis. Long produced by SPSS Inc., it was acquired by IBM in 2009. The current versions (2015) are officially named IBM SPSS Statistics. Companion products in the same family are used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, and collaboration and deployment (batch and automated scoring services). The software name originally stood for Statistical Package for the Social Sciences (SPSS), reflecting the original market, although the software is now popular in other fields as well, including the health sciences and marketing.

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SPSS is a widely used program for statistical analysis in social science. It is also used by market researchers, health researchers, survey companies, government, education researchers, marketing organizations, data miners, and others. The original SPSS manual (Nie, Bent & Hull, 1970) has been described as one of “sociology’s most influential books” for allowing ordinary researchers to do their own statistical analysis. In addition to statistical analysis, data management (case selection, file reshaping, creating derived data) and data documentation (a metadata dictionary was stored in the datafile) are features of the base software.

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Spss free download 16.0 Collect, display and analyze information on applied mathematics SPSS is a sophisticated and competent software system application that integrates, reads and analyzes mathematical information used. Spss 16.0 software, free download For Windows 7 IBM SPSS Statistics is an integrated family of products that offers a rich set of capabilities for every stage of the analytical process. Modules in the IBM SPSS Statistics family can either be purchased individually, or bundled to fit your needs. Dota hotkeys windows 10.

• 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

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