[GUIDE] Open Source & Free Software Programs for Data Analysis for Academic & Scholarly Researchers
By Editorial Staff, Writing Resources Center
Data 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?
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.
Free & Open Source Statistical Computer Programs
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. On the other hand, open-source programs generally come with no costs.
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
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 http://gretl.sourceforge.net/
GNU PSPP: Open-source Alternative to SPSS
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.
It can be used on Microsoft Windows, macOS, and Linux operating systems.
GNU PSPP can be downloaded from https://www.gnu.org/software/pspp/
The R Project for Statistical Computing
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 program is available for Microsoft Windows, macOS, and Linux operating systems.
The R Project for Statistical Computing is available for download at https://www.r-project.org/
JASP
JASP is an open-source free statistical program supported by the University of Amsterdam. The program supports many data formats like .csv, .tsv, .txt, .sav, .por, .sas7bdat, .ods, and .dta.
The software is available for Microsoft Windows, macOS, and Linux. JASP can even be used in a browser using rollApp.
JASP can be downloaded from https://jasp-stats.org/download/
We have tried to provide information on some open source and free statistical computer programs that academic and scholarly researchers and students can use for performing data analysis and presentation for their works.
NOTE: There are many other good open-source computer programs for statistical analysis and can be found on the Internet. If you want us to include any of such computer programs to our list, please drop us a message and our team will review your suggestion for its possible inclusion in our list.
This guide is brought to you by the Writing Resources Center of CSMFL Publications. For more resources, visit Writing Resources Center