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  2. Comparison of statistical packages - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_statistical...

    "A Short Preview of Free Statistical Software Packages for Teaching Statistics to Industrial Technology Majors" (PDF). Journal of Industrial Technology . 21 (2).

  3. SPSS - Wikipedia

    en.wikipedia.org/wiki/SPSS

    SPSS Statistics is a statistical software suite developed by IBM for data management, advanced analytics, multivariate analysis, business intelligence, and criminal investigation. Long produced by SPSS Inc. , it was acquired by IBM in 2009.

  4. LISREL - Wikipedia

    en.wikipedia.org/wiki/LISREL

    von Eye, Alexander; Fuller, Bret E. (2003). "A comparison of the SEM software packages Amos, EQS, and LISREL". Structural Equation Modelling : Applications in Ecological and Evolutionary Biology. New York: Cambridge University Press. pp. 355– 391. ISBN 0-521-78133-7.

  5. PSPP - Wikipedia

    en.wikipedia.org/wiki/PSPP

    PSPP is a free software application for analysis of sampled data, intended as a free alternative for IBM SPSS Statistics. It has a graphical user interface [2] and conventional command-line interface. It is written in C and uses GNU Scientific Library for its mathematical routines. The name has "no official acronymic expansion". [3]

  6. SPSS Modeler - Wikipedia

    en.wikipedia.org/wiki/SPSS_Modeler

    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.

  7. EViews - Wikipedia

    en.wikipedia.org/wiki/EViews

    EViews relies heavily on a proprietary and undocumented file format for data storage. However, for input and output it supports numerous formats, including databank format, Excel formats, PSPP/SPSS, DAP/SAS, Stata, RATS, and TSP. EViews can access ODBC databases. EViews file formats can be partially opened by gretl.

  8. Response surface methodology - Wikipedia

    en.wikipedia.org/wiki/Response_surface_methodology

    In statistics, response surface methodology (RSM) explores the relationships between several explanatory variables and one or more response variables. RSM is an empirical model which employs the use of mathematical and statistical techniques to relate input variables, otherwise known as factors, to the response.

  9. Average variance extracted - Wikipedia

    en.wikipedia.org/wiki/Average_variance_extracted

    This rule is known as Fornell–Larcker criterion. However, in simulation models this criterion did not prove reliable for composite-based structural equation models (e.g., PLS-PM), [2] but indeed proved to be reliable for factor-based structural equation models (e.g., Amos, PLSF-SEM). [3] [4]