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SPSS is a widely used program for statistical analysis in social science. [9] It is also used by market researchers, health researchers, survey companies, government, education researchers, industries, marketing organizations, data miners, [10] and others.
Mondrian – data analysis tool using interactive statistical graphics with a link to R; Neurophysiological Biomarker Toolbox – Matlab toolbox for data-mining of neurophysiological biomarkers; OpenBUGS; OpenEpi – A web-based, open-source, operating-independent series of programs for use in epidemiology and statistics based on JavaScript and ...
IBM SPSS Modeler is a data mining and text analytics software application from IBM.It is used to build predictive models and conduct other analytic tasks. It has a visual interface which allows users to leverage statistical and data mining algorithms without programming.
Statistics education is the practice of teaching and learning of statistics, along with the associated scholarly research. Statistics is both a formal science and a practical theory of scientific inquiry , and both aspects are considered in statistics education.
Integrated data analysis graphing software for science and engineering. Flexible multi-layer graphing framework. 2D, 3D and statistical graph types. Built-in digitizing tool. Analysis with auto recalculation and report generation. Built-in scripting and programming languages. Perl Data Language: Karl Glazebrook 1996 c. 1997 2.080 28 May 2022: Free
SPSS, originally called the Statistical Package for the Social Sciences, is a commercial general statistical analysis program where the data is presented in a spreadsheet layout and common analyses are menu driven.
SPSS Inc. was a software house headquartered in Chicago and incorporated in Delaware, most noted for the proprietary software of the same name SPSS. The company was started in 1968 when Norman Nie , Dale Bent, and Hadlai "Tex" Hull developed and started selling the SPSS software.
Descriptive statistics Nonparametric statistics Quality control Survival analysis Data processing Base stat. [Note 2] Normality tests [Note 3] CTA [Note 4] Nonparametric comparison, ANOVA: Cluster analysis Discriminant analysis BDP [Note 5] Ext. [Note 6]
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