https://mklab.gr/ Sat, 17 Oct 2026 21:24:04 +0000 MyBB https://mklab.gr/showthread.php?tid=1937 Thu, 10 Sep 2026 23:40:12 +0300 mklabgr]]> https://mklab.gr/showthread.php?tid=1937
A major goal of SOFA Statistics is ease of use: its workflow helps users choose appropriate basic statistical tests and specify which variables to analyse, making it particularly suitable for students, educators, researchers, and users who do not want to work primarily through programming. Its statistical capabilities are more limited than those of comprehensive environments such as R, but research comparing menu-driven statistical packages found that SOFA produced broadly comparable results for common calculations such as frequencies, means, correlations, and regression. The software is cross-platform, distributed under the AGPL open-source licence, and its name reflects its aim of making statistical analysis "open for all.

SOFA]]>
A major goal of SOFA Statistics is ease of use: its workflow helps users choose appropriate basic statistical tests and specify which variables to analyse, making it particularly suitable for students, educators, researchers, and users who do not want to work primarily through programming. Its statistical capabilities are more limited than those of comprehensive environments such as R, but research comparing menu-driven statistical packages found that SOFA produced broadly comparable results for common calculations such as frequencies, means, correlations, and regression. The software is cross-platform, distributed under the AGPL open-source licence, and its name reflects its aim of making statistical analysis "open for all.

SOFA]]> https://mklab.gr/showthread.php?tid=578 Mon, 22 Jun 2026 12:11:07 +0300 mklabgr]]> https://mklab.gr/showthread.php?tid=578 free, open-source programming language designed mainly for statistical computing, data analysis, and data visualization. It was created by Ross Ihaka and Robert Gentleman at the University of Auckland in the early 1990s and was strongly influenced by the earlier S programming language. R supports several programming styles, including functional, procedural, and object-oriented programming, and is available on Windows, macOS, and Linux. It is widely used in statistics, data science, bioinformatics, research, and education because it combines powerful mathematical and statistical capabilities with flexible visualization tools. 

A major strength of R is its enormous ecosystem of packages, which extend the language with specialized tools for statistical modelling, machine learning, time-series analysis, data manipulation, scientific reporting, and graphics. Popular collections such as tidyverse simplify data cleaning, transformation, modelling, and visualization, while tools such as R Markdown, Quarto, and knitr support reproducible research and reporting. R can be used through its command line or through environments such as RStudio, Jupyter, and Google Colab, making it suitable for both interactive exploration and larger analytical projects.


R Programming]]> free, open-source programming language designed mainly for statistical computing, data analysis, and data visualization. It was created by Ross Ihaka and Robert Gentleman at the University of Auckland in the early 1990s and was strongly influenced by the earlier S programming language. R supports several programming styles, including functional, procedural, and object-oriented programming, and is available on Windows, macOS, and Linux. It is widely used in statistics, data science, bioinformatics, research, and education because it combines powerful mathematical and statistical capabilities with flexible visualization tools. 

A major strength of R is its enormous ecosystem of packages, which extend the language with specialized tools for statistical modelling, machine learning, time-series analysis, data manipulation, scientific reporting, and graphics. Popular collections such as tidyverse simplify data cleaning, transformation, modelling, and visualization, while tools such as R Markdown, Quarto, and knitr support reproducible research and reporting. R can be used through its command line or through environments such as RStudio, Jupyter, and Google Colab, making it suitable for both interactive exploration and larger analytical projects.


R Programming]]> https://mklab.gr/showthread.php?tid=577 Mon, 22 Jun 2026 12:08:04 +0300 mklabgr]]> https://mklab.gr/showthread.php?tid=577 PSPP is a free and open-source statistical analysis program developed as part of the GNU Project. It was created as a freely available alternative to IBM SPSS Statistics, offering both a graphical interface and a command-line environment. Written mainly in C and using the GNU Scientific Library for mathematical routines, PSPP runs on Linux, Windows, macOS, and other GNU-compatible systems. It began in the late 1990s under the name Fiasco, motivated by the desire to provide statistical software that users could freely copy, modify, and distribute. 

The program supports many common statistical techniques, including descriptive statistics, frequency tables, cross-tabulations, $t$-tests, one-way ANOVA, linear and logistic regression, Cronbach's alpha, chi-square tests, non-parametric tests, factor analysis, cluster analysis, and principal component analysis. It can import data from formats such as CSV, OpenDocument spreadsheets and PostgreSQL databases, while producing tables and graphs in formats including PDF, HTML, SVG and PostScript. Because it is free and relatively similar to SPSS, PSPP is particularly useful for students, educators, researchers and organizations that need statistical analysis without the cost of proprietary software.

SOFTWARE]]> PSPP is a free and open-source statistical analysis program developed as part of the GNU Project. It was created as a freely available alternative to IBM SPSS Statistics, offering both a graphical interface and a command-line environment. Written mainly in C and using the GNU Scientific Library for mathematical routines, PSPP runs on Linux, Windows, macOS, and other GNU-compatible systems. It began in the late 1990s under the name Fiasco, motivated by the desire to provide statistical software that users could freely copy, modify, and distribute. 

The program supports many common statistical techniques, including descriptive statistics, frequency tables, cross-tabulations, $t$-tests, one-way ANOVA, linear and logistic regression, Cronbach's alpha, chi-square tests, non-parametric tests, factor analysis, cluster analysis, and principal component analysis. It can import data from formats such as CSV, OpenDocument spreadsheets and PostgreSQL databases, while producing tables and graphs in formats including PDF, HTML, SVG and PostScript. Because it is free and relatively similar to SPSS, PSPP is particularly useful for students, educators, researchers and organizations that need statistical analysis without the cost of proprietary software.

SOFTWARE]]> https://mklab.gr/showthread.php?tid=565 Mon, 22 Jun 2026 10:50:31 +0300 mklabgr]]> https://mklab.gr/showthread.php?tid=565 LabPlot is a free, open-source, cross-platform application for scientific data analysis and visualization, available for Windows through the Microsoft Store. It lets users import data from spreadsheets and external files, organize datasets, and create publication-quality 2D plots and graphics. It supports mathematical function plotting, curve fitting with predefined or custom models, data smoothing, statistical analysis, and signal analysis, making it suitable for students, teachers, scientists, and researchers. 

A particularly powerful feature of LabPlot is its computational notebook interface, which can work with tools and languages such as Python, R, Julia, Maxima, Octave, Sage, and Scilab, allowing calculations and visualizations to be combined in one environment. Graphs can be extensively customized and exported in bitmap or vector formats for reports and publications. LabPlot is distributed under the GPL-2.0+ licence, so it can be freely used, shared, studied, and modified, providing an open-source alternative to commercial scientific plotting packages such as OriginLab and SigmaPlot.


LABPLOT]]> LabPlot is a free, open-source, cross-platform application for scientific data analysis and visualization, available for Windows through the Microsoft Store. It lets users import data from spreadsheets and external files, organize datasets, and create publication-quality 2D plots and graphics. It supports mathematical function plotting, curve fitting with predefined or custom models, data smoothing, statistical analysis, and signal analysis, making it suitable for students, teachers, scientists, and researchers. 

A particularly powerful feature of LabPlot is its computational notebook interface, which can work with tools and languages such as Python, R, Julia, Maxima, Octave, Sage, and Scilab, allowing calculations and visualizations to be combined in one environment. Graphs can be extensively customized and exported in bitmap or vector formats for reports and publications. LabPlot is distributed under the GPL-2.0+ licence, so it can be freely used, shared, studied, and modified, providing an open-source alternative to commercial scientific plotting packages such as OriginLab and SigmaPlot.


LABPLOT]]> https://mklab.gr/showthread.php?tid=554 Mon, 22 Jun 2026 06:44:16 +0300 mklabgr]]> https://mklab.gr/showthread.php?tid=554 jamovi is a free, open-source statistical software platform designed to make data analysis accessible to students, educators, and researchers. It provides a familiar spreadsheet-style interface where users can import data, select variables, and perform statistical analyses without writing code. Results and graphs update automatically as options are changed. Although jamovi is designed for ease of use, it is powered by the R statistical language, and users can view the R syntax underlying their analyses, making it useful both for beginners and for those learning reproducible statistical computing. 

The software is available both as a completely free desktop application, which can operate offline and keep data locally, and as jamovi Cloud, which runs in a web browser and is convenient for classrooms, computer labs, Chromebooks, and tablets. Its functionality can also be expanded through a library of community-developed statistical modules. Analyses, data, and results can be stored together in a single shareable file, supporting reproducible research and teaching. According to the project, jamovi has surpassed 5 million downloads, is used at more than 300 universities, and offers over 70 library modules. 


JAMOVI]]> jamovi is a free, open-source statistical software platform designed to make data analysis accessible to students, educators, and researchers. It provides a familiar spreadsheet-style interface where users can import data, select variables, and perform statistical analyses without writing code. Results and graphs update automatically as options are changed. Although jamovi is designed for ease of use, it is powered by the R statistical language, and users can view the R syntax underlying their analyses, making it useful both for beginners and for those learning reproducible statistical computing. 

The software is available both as a completely free desktop application, which can operate offline and keep data locally, and as jamovi Cloud, which runs in a web browser and is convenient for classrooms, computer labs, Chromebooks, and tablets. Its functionality can also be expanded through a library of community-developed statistical modules. Analyses, data, and results can be stored together in a single shareable file, supporting reproducible research and teaching. According to the project, jamovi has surpassed 5 million downloads, is used at more than 300 universities, and offers over 70 library modules. 


JAMOVI]]> https://mklab.gr/showthread.php?tid=553 Mon, 22 Jun 2026 06:42:04 +0300 mklabgr]]> https://mklab.gr/showthread.php?tid=553 Orange Data Mining is a free, open-source platform for machine learning, data analysis, and interactive visualization. Its main strength is its visual programming approach: users build analysis workflows by placing widgets on a canvas and connecting them, making it possible to explore datasets, train models, and evaluate results with little or no programming. Orange includes tools for statistical distributions, scatter plots, decision trees, clustering, heatmaps, multidimensional visualization, t-SNE, and other common data-science techniques. 

Orange can also be expanded with add-ons for areas such as text mining and natural language processing, network analysis, association rules, time-series analysis, survival data, spectroscopy, and bioinformatics. It is particularly well suited to education because teachers can demonstrate machine-learning concepts visually and students can experiment with real datasets without first mastering a programming language. The project provides documentation, tutorials, example workflows, workshops, and developer resources, and is used in schools, universities, research laboratories, and professional training. 

ORANGE]]> Orange Data Mining is a free, open-source platform for machine learning, data analysis, and interactive visualization. Its main strength is its visual programming approach: users build analysis workflows by placing widgets on a canvas and connecting them, making it possible to explore datasets, train models, and evaluate results with little or no programming. Orange includes tools for statistical distributions, scatter plots, decision trees, clustering, heatmaps, multidimensional visualization, t-SNE, and other common data-science techniques. 

Orange can also be expanded with add-ons for areas such as text mining and natural language processing, network analysis, association rules, time-series analysis, survival data, spectroscopy, and bioinformatics. It is particularly well suited to education because teachers can demonstrate machine-learning concepts visually and students can experiment with real datasets without first mastering a programming language. The project provides documentation, tutorials, example workflows, workshops, and developer resources, and is used in schools, universities, research laboratories, and professional training. 

ORANGE]]> https://mklab.gr/showthread.php?tid=552 Mon, 22 Jun 2026 06:39:17 +0300 mklabgr]]> https://mklab.gr/showthread.php?tid=552 JASP

Summary

JASP is a free, open-source, cross-platform statistical analysis program developed with support from the University of Amsterdam. It provides a user-friendly graphical interface similar to spreadsheet software, allowing researchers, students, and data analysts to perform statistical tests without programming. 

JASP supports both traditional (frequentist) and Bayesian methods, including t-tests, ANOVA, regression, correlation, contingency tables, meta-analysis, and more, with dynamic results, publication-ready APA-style tables, and integration features that support reproducible research and open science. Its main goal is to make advanced statistical analysis—especially Bayesian statistics—more accessible while remaining free, flexible, and easy to learn. 

SOFTWARE PAGE]]> JASP

Summary

JASP is a free, open-source, cross-platform statistical analysis program developed with support from the University of Amsterdam. It provides a user-friendly graphical interface similar to spreadsheet software, allowing researchers, students, and data analysts to perform statistical tests without programming. 

JASP supports both traditional (frequentist) and Bayesian methods, including t-tests, ANOVA, regression, correlation, contingency tables, meta-analysis, and more, with dynamic results, publication-ready APA-style tables, and integration features that support reproducible research and open science. Its main goal is to make advanced statistical analysis—especially Bayesian statistics—more accessible while remaining free, flexible, and easy to learn. 

SOFTWARE PAGE]]>