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There are a few reviews of free statistical software. There were two reviews in journals (but not peer reviewed), one by Zhu and Kuljaca [26] and another article by Grant that included mainly a brief review of R. [27] Zhu and Kuljaca outlined some useful characteristics of software, such as ease of use, having a number of statistical procedures and ability to develop new procedures.
SuperCROSS – comprehensive statistics package with ad-hoc, cross tabulation analysis; Systat – general statistics package; The Unscrambler – free-to-try commercial multivariate analysis software for Windows; Unistat – general statistics package that can also work as Excel add-in; WarpPLS – statistics package used in structural ...
JASP (Jeffreys’s Amazing Statistics Program [2]) is a free and open-source program for statistical analysis supported by the University of Amsterdam. It is designed to be easy to use, and familiar to users of SPSS. It offers standard analysis procedures in both their classical and Bayesian form.
PDF-XChange: PDF Tools and PDF-XChange print driver allow conversion from many formats to PDF. A "lite" version of the print driver is free for non-commercial (home and academic) but places a watermark on documents; Qiqqa: Converts Microsoft Word document and Web Pages to PDF.
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]
This is a list of free and open-source software packages, computer software licensed under free software licenses and open-source licenses. Software that fits the Free Software Definition may be more appropriately called free software; the GNU project in particular objects to their works being referred to as open-source. [1]
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LISREL (linear structural relations) is a proprietary statistical software package used in structural equation modeling (SEM) for manifest and latent variables. It requires a "fairly high level of statistical sophistication".