9 Best Free Statistical Software of 2026

1. 1

   R and RStudio

   R is a free language and environment for statistical computing and graphics, and RStudio is Posit's free open source IDE for working in it.

   9.6overall

   R is a free language and environment for statistical computing and graphics, and RStudio is Posit's free open source IDE for working in it.

   Best forresearchers and analysts who will write code

   Adoption data

   350+ packages, millions weeklyPosit, the company behind RStudio and the tidyverse, says its 350+ open source packages are used by millions of people every week.

   Posit, RStudio IDE (2026): “We build RStudio, the tidyverse, Shiny, Quarto, and 350+ packages used by millions of people every week.”

   R is the reference free statistics environment: the R Project describes it as free software for statistical computing and graphics that runs on UNIX platforms, Windows and macOS, and version 4.6.2 shipped on October 29, 2026. Most people use it through RStudio, Posit's open source IDE, which adds a code editor with completion and diagnostics, a data viewer with sorting and histogram filters, an interactive debugger, Git integration and a visual editor for Quarto and R Markdown reports. Posit says it builds RStudio, the tidyverse, Shiny, Quarto and 350+ packages used by millions of people every week, and its RStudio page promises that using RStudio without AI will cost nothing. The trade-off is the learning curve: every analysis is a script, so students who only need a t-test or ANOVA once a semester may move faster in jamovi or JASP. Posit AI, the optional assistant, costs $20 per month. We compared documented features and published prices; we did not run hands-on tests.

   Strengths

   • +Both R and the RStudio open source edition cost nothing
   • +Posit states RStudio will remain free without AI
   • +Publishes reports and Shiny apps to Posit Connect, shinyapps.io and RPubs

   Limitations

   • −Analysis is done by writing R code, with no point-and-click menus for tests
   • −Posit AI assistance is an add-on at $20 per month
   • −RStudio open source is AGPL v3; organizations that cannot use AGPL software need RStudio Desktop Pro at $1,204 per year

   SummaryR and RStudio is the best free statistical software for people willing to write code, because the language and the RStudio open source IDE cost nothing and Posit says its packages reach millions of users weekly. Pick jamovi or JASP if you want menus instead of scripts.

2. 2

   jamovi

   Free, open statistical spreadsheet built on R, available as a desktop app and in the browser.

   9.0overall

   Free, open statistical spreadsheet built on R, available as a desktop app and in the browser.

   Best forstudents and instructors moving off SPSS

   Adoption data

   5M+ downloadsjamovi reports more than 5 million downloads and use at more than 300 universities.

   jamovi project, jamovi: open statistical software (2026): “5M+ Downloads 300+ Universities”

   jamovi calls itself a free and open statistical spreadsheet and pitches itself directly as an alternative to costly proprietary stats products. You drag variables into an analysis, choose options and the results table updates as you click, with no code required. Under the hood it runs R, and jamovi can show the exact R syntax behind each analysis, which helps students who will later move to scripts. The desktop app works fully offline and keeps data on your own computer, while jamovi Cloud runs in a browser on any device, including Chromebooks and tablets, which makes it practical for teaching labs. jamovi reports 5M+ downloads, 300+ universities and 70+ library modules. Testimonials on its site come from departments that switched from SPSS. The limit is scope: you get what the menus and modules cover, so niche models still need R. We compared documented features and published prices; we did not run hands-on tests.

   Strengths

   • +Desktop version is free with no time limit
   • +Browser version needs no install, which suits computer labs
   • +R syntax view lets students graduate to code

   Limitations

   • −Analyses are limited to what the built-in menus and installed modules offer
   • −The free cloud option is the Guest plan; offline work needs the desktop install
   • −Fewer citations than R itself in published research

   Summaryjamovi is the best free point-and-click statistics program for students leaving SPSS, because the desktop app is free forever and it reports use at 300+ universities. Choose R if you need models outside its menus and modules.

3. 3

   JASP

   Free, open source statistics program from the University of Amsterdam that runs classical and Bayesian analyses through menus.

   9.0overall

   Free, open source statistics program from the University of Amsterdam that runs classical and Bayesian analyses through menus.

   Best forresearchers who want Bayesian tests without code

   Adoption data

   Leading R GUI by citationsIn r4stats.com's count of scholarly articles citing statistics software, JASP and jamovi lead all other graphical front ends to R by a wide margin.

   Robert A. Muenchen, r4stats.com, The Popularity of Data Science Software (2022): “JASP and jamovi are both front-ends to the R language and are way out front in this category.”

   JASP is an open source project supported by the University of Amsterdam, and its team describes it as a free cross-platform program with a modern graphical interface. Its signature feature is that standard procedures come in both classical and Bayesian form, so a t-test, ANOVA or regression can be reported with Bayes factors without writing code. Output updates as you change options, tables and graphs copy into Word in APA format, and results can be linked to the Open Science Framework. JASP opens SPSS, SAS, CSV and OpenDocument files, which makes switching from paid packages straightforward. In r4stats.com's citation counts, JASP and jamovi lead the other R front ends by a wide margin. The FAQ says the engine is GPLv2 and the desktop is AGPL v3. What it lacks is a code console for models outside its menus, so heavy modelers still need R or Python. We compared documented features and published prices; we did not run hands-on tests.

   Strengths

   • +Free on Windows, macOS and Linux
   • +Bayesian tests sit next to classical ones in the same menus
   • +Reads SPSS and SAS data files directly

   Limitations

   • −No scripting window for custom models like R or Python
   • −Desktop interface is under the GNU Affero GPL v3, which some organizations review before use
   • −Fewer add-on modules than R's package ecosystem

   SummaryJASP is the best free choice for researchers who want Bayesian and classical tests side by side, because both come in the same menus at no cost. Pick R if you need custom models.

4. 4

   Python with statsmodels

   Open source Python module for estimating statistical models, running hypothesis tests and exploring data.

   8.9overall

   Open source Python module for estimating statistical models, running hypothesis tests and exploring data.

   Best foranalysts and data scientists who already use Python

   statsmodels is the main statistics library in Python. Its documentation describes classes and functions for estimating many different statistical models, running statistical tests and exploring data, with an extensive list of result statistics for each estimator. Models can be written with R-style formulas against pandas DataFrames, so an ordinary least squares regression takes a few lines and prints a full summary table. The project says results are tested against existing statistical packages to check they are correct, and the Modified BSD license allows commercial use without the copyleft terms that apply to some tools on this list. Version 0.15.0 was released on August 27, 2026. It pairs naturally with SciPy for distributions and tests and with pandas for data handling. The cost is that everything is code: there are no menus, so it is a poor fit for a first statistics course. We found no citable usage figure from the project, so we scored adoption conservatively. We compared documented features and published prices; we did not run hands-on tests.

   Strengths

   • +Permissive BSD license suits commercial use
   • +Fits into existing Python, pandas and Jupyter workflows
   • +Developers test results against other statistical packages

   Limitations

   • −No graphical interface; every step is code
   • −Needs Python, pandas and SciPy installed alongside it
   • −Fewer specialized methods than R's package repository

   SummaryPython with statsmodels is the best free option for analysts already working in Python, because it adds statistical models and tests to Python under a permissive BSD license. Pick jamovi or JASP if you do not code.

5. 5

   KNIME Analytics Platform

   Free, open source desktop platform for building data analysis workflows from visual nodes, with optional Python and R scripting.

   8.5overall

   Free, open source desktop platform for building data analysis workflows from visual nodes, with optional Python and R scripting.

   Best forbusiness analysts who prefer visual workflows

   Adoption data

   100,000+ usersKNIME says more than 100,000 people are part of the open community of KNIME Analytics Platform users.

   KNIME, KNIME Analytics Platform (2026): “Join the open community of over 100,000+ KNIME Analytics Platform users”

   KNIME Analytics Platform is a free, open source desktop tool where you build an analysis by connecting nodes on a canvas rather than writing code. KNIME lists 300+ connectors to data sources, and its nodes aggregate, sort, filter and join data, then run analytic techniques with access to popular machine learning libraries. When a node is missing you can drop in Python, R or JavaScript, and a genAI assistant can draft workflows and charts from prompts. KNIME says its open community has over 100,000 users and its Community Hub holds 14,000+ shared solutions, which helps beginners copy working examples. For statistics it is strongest at repeatable data preparation and predictive modeling; classic hypothesis tests are less central than in jamovi or JASP. Paid KNIME Hub plans for team sharing are priced by quote. We compared documented features and published prices; we did not run hands-on tests.

   Strengths

   • +Free desktop platform with no per-seat license
   • +Workflows are saved and reused, unlike one-off menu clicks
   • +Calls R and Python when a node is missing

   Limitations

   • −Built for data preparation and machine learning more than classic hypothesis testing
   • −Workflow canvas takes longer to learn than SPSS-style menus
   • −Team collaboration features sit in paid KNIME Hub plans priced by quote

   SummaryKNIME Analytics Platform is the best free choice for analysts who want repeatable visual workflows, because the desktop platform is free and connects to 300+ data sources. Pick jamovi for classroom hypothesis testing.

6. 6

   SAS OnDemand for Academics

   Free cloud access to SAS Studio for students, educators and independent learners.

   8.4overall

   Free cloud access to SAS Studio for students, educators and independent learners.

   Best forstudents who need SAS skills for jobs or courses

   Adoption data

   150+ countriesSAS says it has customers in more than 150 countries.

   SAS Institute, SAS company information (2026): “150+ countries with SAS customers”

   SAS OnDemand for Academics is how most people get SAS for free. SAS describes it as a free, cloud-based learning environment where students, educators and independent learners use SAS Studio to program, run statistical analysis and work with data without installing software. Instructors who want a point-and-click Windows interface can register a course for SAS Enterprise Guide. Everyone gets up to 5GB of storage in the SAS Cloud, educators get an extra 3GB for course data, and two e-learning courses, Programming 1 and Statistics 1, are included. Learners without a college affiliation can still sign up for SAS Studio. SAS says it has customers in more than 150 countries, which is why SAS skills still appear in analyst job requirements. The catch is the license: it is for teaching and learning, so you cannot run client or company work on it, and it only runs in the cloud. We compared documented features and published prices; we did not run hands-on tests.

   Strengths

   • +Real SAS software at no cost for learning
   • +Includes free courses that prepare for SAS skills
   • +Educators get an extra 3GB for course data

   Limitations

   • −Licensed for teaching and learning, not commercial work
   • −Runs only in the cloud with a 5GB personal data limit
   • −Enterprise Guide access requires an instructor-registered course

   SummarySAS OnDemand for Academics is the best free way to learn SAS, because SAS Studio and two e-learning courses are free for students and independent learners. Pick R or jamovi for work you will use commercially.

7. 7

   Orange Data Mining

   Free, open source visual programming tool for data visualization and machine learning from the University of Ljubljana.

   8.3overall

   Free, open source visual programming tool for data visualization and machine learning from the University of Ljubljana.

   Best forteachers and beginners exploring data visually

   Adoption data

   Fastest-growing workflow toolIn r4stats.com's analysis of scholarly citations, Orange Data Mining was the fastest growing workflow-based analytics tool.

   Robert A. Muenchen, r4stats.com, The Popularity of Data Science Software (2022): “Of the workflow-based tools, Orange Data Mining is growing the fastest.”

   Orange is a free, open source tool for machine learning and data visualization developed at the University of Ljubljana. You build an analysis by placing widgets on a canvas and connecting them, then explore distributions, box plots and scatter plots or move on to decision trees, hierarchical clustering, heatmaps, MDS and t-SNE. Add-ons extend it to text mining, network analysis, time series, spectra and gene expression data. Orange is widely used in teaching and includes widgets designed for that purpose, and r4stats.com found it was the fastest growing workflow-based tool in scholarly citations. It is licensed under the GNU GPL, and the current release is 3.40.0. For a statistics course it is better at showing what data looks like and how models behave than at producing a full table of t-tests, chi-square tests and ANOVA output, where jamovi and JASP are stronger. We compared documented features and published prices; we did not run hands-on tests.

   Strengths

   • +Free under the GNU GPL
   • +Very visual, suited to classroom demonstrations
   • +Add-ons cover domain-specific data such as spectra and gene expression

   Limitations

   • −Focused on machine learning and visualization, with fewer classic statistical tests than jamovi or JASP
   • −Large workflows can get crowded on the canvas
   • −No published user count from the project

   SummaryOrange Data Mining is the best free choice for visual data exploration and teaching machine learning, because its widgets need no code and it is GPL licensed. Pick jamovi or JASP for standard hypothesis tests.

8. 8

   JMP Student Edition

   Free academic version of JMP's menu-driven statistical discovery software for eligible students, instructors and researchers.

   8.2overall

   Free academic version of JMP's menu-driven statistical discovery software for eligible students, instructors and researchers.

   Best forenrolled students and academic researchers

   Adoption data

   Hundreds of thousandsJMP says its software is the tool of choice for hundreds of thousands of data explorers.

   JMP Statistical Discovery, JMP Student Edition (2026): “JMP is the tool of choice for hundreds of thousands of data explorers.”

   JMP Student Edition gives the menu-driven JMP statistical software to qualified students, instructors and academic researchers at no cost. Eligibility requires being enrolled or employed at a degree-granting institution, and the license is renewed every 12 months for as long as you qualify. The capability list is broad: data import and management, regression and ANOVA, multivariate analysis, structural equation modeling, time series forecasting, design of experiments, reliability and survival analysis, statistical quality control and Six Sigma. Every analysis is paired with a graph, which helps students read results. JMP says its software is the tool of choice for hundreds of thousands of data explorers, and it is used in many statistics textbooks. The limits are who can use it and for what: independent learners and companies do not qualify, so it is not a long-term replacement for a paid package outside academia. We compared documented features and published prices; we did not run hands-on tests.

   Strengths

   • +Full menu of advanced methods, including design of experiments
   • +Renewable at no cost every 12 months while eligible
   • +Each statistical result comes with a matching graph

   Limitations

   • −Only for people enrolled or employed at a degree-granting institution
   • −Must be renewed every 12 months
   • −Commercial JMP licenses are paid, so skills do not come with a free work license

   SummaryJMP Student Edition is the best free choice for enrolled students who need design of experiments and quality tools, because the full menu-driven JMP is free while you are eligible. Pick jamovi if you are not affiliated with a university.

9. 9

   GNU PSPP

   Free GNU replacement for SPSS with similar menus and compatible syntax and data files.

   7.2overall

   Free GNU replacement for SPSS with similar menus and compatible syntax and data files.

   Best forusers who want SPSS-style syntax for free

   GNU PSPP is a free replacement for SPSS that looks and works much like it. Its home page states there are no time bombs, no artificial limits on cases or variables and no add-on packages to buy, and it supports over 1 billion cases and over 1 billion variables. Syntax and data files are compatible with SPSS, so existing SPSS syntax and data files carry over. Procedures cover descriptive statistics, t-tests, ANOVA, linear and logistic regression, measures of association, cluster analysis, reliability and factor analysis and non-parametric tests, with output to text, PDF, OpenDocument or HTML. You can use a graphical interface or run syntax from a terminal. The project names GNU/Linux as its preferred platform. PSPP covers fewer procedures than SPSS itself and lacks the modern interfaces of jamovi or JASP, and we found no citable usage figure, so its adoption score is conservative. We compared documented features and published prices; we did not run hands-on tests.

   Strengths

   • +Runs existing SPSS syntax and opens SPSS data files
   • +No case or variable limits and no expiry
   • +All functions are in the core package with nothing extra to buy

   Limitations

   • −Narrower set of procedures than SPSS, jamovi or R
   • −GNU/Linux is the preferred platform; other systems rely on community reports
   • −No published user count, so adoption is hard to judge

   SummaryGNU PSPP is the best free choice for people who need to run existing SPSS syntax, because it reads SPSS syntax and data files with no license fees. Pick jamovi for a more modern interface and wider analyses.

Questions or corrections: editorial@statlyst.com · Disclosure