Jamovi Desktop is a free, open-source statistical analysis application that combines a spreadsheet interface with R-powered methods for researchers, students, and educators working with quantitative data.
Jamovi Desktop is an open-source statistics application that lets users organize data, run analyses, and inspect results through a spreadsheet-style interface. It is designed for students learning statistical methods, educators preparing practical exercises, and researchers who need an accessible alternative to command-driven workflows. Users can import a dataset, assign variable types, select an analysis, and adjust its options while viewing the resulting tables and figures. The application uses R as its statistical engine, connecting familiar graphical controls with established analytical methods. This approach makes it possible to concentrate on research questions and interpretation without requiring programming knowledge for routine statistical work.
The Windows installer supplied here is a 64-bit build of the 2.7.38 release, which the project identifies as part of its Solid release series. Jamovi Desktop can operate locally without a continuous internet connection, while optional modules may require network access for installation. Its native project format preserves data, analysis settings, and results together, allowing work to be reopened without reconstructing every procedure. For remote access to a computer containing an existing statistical project, Chrome Remote Desktop can provide a separate way to reach that machine. The desktop application is distinct from the browser-based cloud service, so users should choose the deployment that fits their storage and access requirements.
Jamovi Desktop reduces the effort required to move from a dataset to interpretable statistical results while keeping the analytical process visible. Students can practice established methods without purchasing a commercial statistics license, and instructors can distribute exercises that use the same application across a class. Researchers benefit from retaining analysis choices alongside their data, which makes it easier to revisit decisions, check calculations, and share a project with collaborators. The graphical workflow also helps users compare alternative models without repeatedly rebuilding an entire analysis from scratch. Because the application runs locally, sensitive datasets do not need to be uploaded to a cloud service simply to perform routine calculations. Its connection to R provides a useful progression for users who later want to inspect or extend their statistical work through code. Together, these advantages support more consistent teaching, clearer review of research decisions, and a practical path from introductory statistics to more specialized analysis.
The spreadsheet editor lets users enter observations, inspect variables, and prepare datasets directly inside Jamovi Desktop. Columns can be assigned appropriate measurement types, while computed variables and filters support common preparation tasks. This keeps data management close to the analysis workspace and reduces the need to switch between separate applications for routine changes.
The core analysis collection includes descriptive statistics, t-tests, analysis of variance, correlation, regression, contingency tables, and factor-related methods. Users select variables and configure options through graphical controls rather than writing commands. These tools cover many introductory and applied research tasks, while more specialized procedures can be added through the module system.
Analysis results update when relevant data or selected options change, allowing users to examine the consequences of their decisions without manually rerunning every procedure. Jamovi Desktop displays output alongside the working dataset, making it easier to compare alternative settings and identify unexpected results. This interactive behavior is particularly useful during exploratory analysis and classroom demonstrations.
The application can open common research and spreadsheet formats, including CSV, Excel, SPSS, SAS, and Stata files. This allows users to bring existing datasets into Jamovi Desktop without first rebuilding them manually. Supported import formats help researchers move between statistical environments, although imported files should still be checked for correct variable types and missing-value handling.
Jamovi Desktop uses R for statistical computation and can display the R syntax associated with graphical analyses. Users can inspect or copy that syntax when they need a more transparent record of their analytical choices. The optional Rj editor also supports running R code within the application, providing a route toward more customized statistical workflows.
The module system adds statistical procedures beyond the standard installation, including specialized approaches such as mixed models, meta-analysis, and Bayesian methods. Users can browse available extensions and install those relevant to their research. Module availability and compatibility depend on the installed release, so checking the library before planning a specialized workflow is advisable.
Jamovi Desktop saves datasets, analysis configurations, and results in its native project format. Reopening a project restores the analytical context, making it easier to continue work or review how a result was produced. Sharing the project file can also help collaborators inspect the same data and settings, subject to appropriate permissions and data-sharing requirements.
The application provides graphical output for exploring distributions, relationships, and statistical results, including common charts such as histograms, scatterplots, and box plots. Plot options can be adjusted within the analysis workflow, and figures can be exported for use in reports. Visual inspection helps users identify patterns and assess whether numerical summaries adequately describe their data.
Yes. The desktop application is free and open source. Its source code is available under the AGPL-3.0 license, and the project provides the desktop software without a commercial license fee.
The installed desktop application can run statistical analyses locally without a continuous internet connection. Internet access may be needed to download the installer, obtain updates, or install additional modules from the online library.
Yes. It supports common data formats including SPSS SAV, Excel XLSX, CSV, SAS, and Stata files. After importing a dataset, check variable types, labels, and missing values before running analyses.
Jamovi provides a graphical interface for statistical analysis and uses R as its computational engine. R is a programming language and environment that offers broader scripting and customization capabilities. Jamovi can display R syntax, and optional tools allow users to run R code within the application.
Open the module library from the application and browse the available extensions. Select a compatible module to install it, then access its analyses through the relevant menus. If the library cannot be reached, check the network connection and consult the project's documentation or community forum.
Yes. The native OMV project format stores the dataset, analysis settings, and results together. This allows you to reopen a project and continue working without recreating the analysis configuration.
Version 2.7.38.0 is the supplied Windows installer and belongs to the project's Solid release series. The official release history dates version 2.7.38 to July 21, 2026. The project also maintains a newer Current series, so check the official download page if you want the latest available release rather than this specific installer.
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