![]() ![]() Open Source & Free Software Programs for Data Analysis for Academic & Scholarly Researchersīy Editorial Staff, Writing Resources Centerĭata analysis holds prime importance for academic & scholarly researchers to support their findings and conclusions. The scholarly authors need to process a lot of data for their domain studies, because they need to draw relevant and considerate meanings out of this data. The data more or less needs to be processed for certain statistical methods and models. Processing data manually was more of a headache before we have statistical computer programs to do the job. What do these statistical computer programs do? Free & Open Source Statistical Computer Programs They can be used to plot data, present data graphically, export data in a more reader/user-friendly manner, carry out statistical and mathematical calculations and output depiction. Most proprietary software programs for statistical analysis are paid and costly. Academic & scholarly researchers, especially research students, may wish here to know about some useful, free and open-source software programs that they can use out of the box to perform data analysis for their researches/studies. Open-source software programs make their source code available to the public in an open and transparent manner. Using open-source software may require more learning efforts than the proprietary software programs. While proprietary software programs are user-friendly and more polished, they come with a cost. So, here below are some open-source computer programs that academic & scholarly researchers and authors can use for free: Gretl: Gnu Regression, Econometrics and Time-series Library On the other hand, open-source programs generally come with no costs. Gretl or Gnu Regression, Econometrics and Time-series Library is a software package for econometric analysis, written in the C programming language which is available on Microsoft Windows, Mac OS X, and Linux. The software can be downloaded from GNU PSPP: Open-source Alternative to SPSS #PSPP DOWNLOAD FOR WINDOWS MAC OS# ![]() GNU PSPP, a cross-platforms software program, can perform descriptive statistics, T-tests, ANOVA, linear and logistic regression, measures of association, cluster analysis, reliability and factor analysis, non-parametric tests and more. GNU PSPP can be downloaded from The R Project for Statistical Computing It can be used on Microsoft Windows, macOS, and Linux operating systems. R Project for Statistical Computing, a statistical analysis and graphic tool supports a variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, etc.) and graphical techniques. The R Project for Statistical Computing is more of an environment with implemented statistical methods & techniques and is maintained by The R Foundation. The R Project for Statistical Computing is available for download at JASP The program is available for Microsoft Windows, macOS, and Linux operating systems. ![]() It is a Free replacement for the proprietary program SPSS, and appears very similar to it with a few exceptions. Previous development versions were provided by Jure Čuhalev, but his packages were not updated very frequently.JASP is an open-source free statistical program supported by the University of Amsterdam. GNU PSPP is a program for the statistical analysis of sampled data. Beta version is development version, which contains all new features, but is not thoroughly tested as stable version. In Ubuntu you can install PSPP directly from your browser, from Ubuntu Software Center or with the following command: sudo apt-get install psppĪdam Zammit is providing a beta version of PSPP from his PPA PSPP repository at Launchpad. In Ubuntu Quantal repositories there is available PSPP (0.7.9). PSPP is included in repositories of all main Linux distributions, however in some distributions there are only old versions of PSPP available (0.6.x). Master branch of the PSPP, with newer features, but less testing are available for Ubuntu Linux, Microsoft Windows and Mac OS. However, binary builds are mostly for a stable branch. Source code and official binary downloads are available on a PSPP GNU-org website. ![]()
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