OpenStat for Windows download

Product snapshot

OpenStat is a complimentary Windows program built to help with statistical analysis and basic data handling. It aims to be a straightforward toolkit for performing computations, organizing datasets, and producing results without a steep learning curve or licensing costs.

Intended users

Researchers conducting empirical analyses
Educators teaching statistics or data methods
Students learning statistical techniques

Core capabilities

Exportable reports and summaries that make sharing results simple
Tools for entering, cleaning, and organizing datasets
A selection of common statistical procedures for hypothesis testing and description
An approachable interface that reduces setup time for new projects
Available at no charge, making it suitable for budget-conscious users

Where it fits

This program is categorized for educational and reference use, with a focus on scientific and academic applications. It’s well suited to classrooms, labs, and independent study where basic to moderate statistical work is required.

Alternate option

MaxStat Lite (free) — a lightweight, no-cost alternative that offers a comparable set of features for Windows users who want another option for statistical computing.

Technical

Title

OpenStat

Requirements

Windows

Language

No language has been specified.

Available languages

License

Free

Latest update

2025-10-21

Author

Statpages

Other Useful Business Software

Our Free Plans just got better! | Auth0

With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.

You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.

Try free now

Rate This App

User Reviews

Be the first to post a review of OpenStat!

Related Software

SigmaPlot

SigmaPlot is a scientific graphing and data-analysis application for producing publication-quality figures and combining multiple data sets with fine control over plot appearance. It supports a wide range of visualizations — including 3D surface/mesh plots, contour and volumetric displays, high-resolution 2D charts (scatter, line, bar), heatmaps, histograms, and multi-panel layouts — and offers extensive styling controls for colors, symbols, axes and annotations. Built-in analysis tools include common statistical procedures, nonlinear curve fitting, linear and multiple regression, hypothesis tests, and output tables and fit diagnostics to help interpret results. The software is aimed at researchers, laboratory staff and students who need clear, presentation-ready graphics and analytical rigor for reports, posters, publications or exploratory and confirmatory analyses. For users with simpler needs, MaxStat Lite is a no-cost alternative that handles common plots and basic statistical tests, though it offers less customization and advanced modeling capability.

jamovi 2.3.28.0

jamovi is a free, open-source statistics package that offers an approachable, visual workspace designed to let users perform advanced analyses without a steep learning curve. It emphasizes drag-and-drop simplicity while bundling common statistical procedures, including regression modeling, hypothesis testing, and data visualization, so both newcomers and experienced analysts can work efficiently. Advanced users can extend functionality by integrating external tools and scripts, and results are easy to export and share for reporting and collaboration. Its combination of usability and extensibility makes it well suited for researchers, instructors, students, and anyone needing routine or advanced statistical analysis for classroom teaching, lab research, or individual data projects.

MEGA12

MEGA12 is a free application for analyzing DNA and protein sequences, designed to handle large collections of gene data. It provides sequence alignment, statistical model selection and hypothesis testing, and tools for phylogenetic reconstruction and tree exploration, backed by high-performance algorithms and built-in statistical routines. It supports batch workflows and exportable graphical outputs for publication-quality figures, making it useful for evolutionary biologists, bioinformaticians, educators, and students. Its combination of speed, usability, and specialized analytical methods facilitates exploration of sequence variation, testing of evolutionary hypotheses, and visualization of phylogenetic results.

jamovi 2.6.44.0

jamovi 2.6.44.0 is an open-source statistics package that pairs an approachable, intuitive interface with tools suitable for advanced analyses. It offers real-time updates to results as analyses change, flexible data import/export, interoperability with R for scriptable extensions, and a broad set of built-in statistical procedures and charting options. It’s well suited for students, researchers, and professionals who want to perform sophisticated analyses without extensive programming, or who prefer visual, interactive results while retaining the option to extend functionality with R. If your main need is quick cross-device file transfer rather than statistical computing, a file-sharing tool like SHAREit can be a convenient complementary option.

jamovi 2.6.26.0

jamovi is a free, open-source statistics application with an approachable graphical interface that supports a wide range of analyses for both beginners and experienced users. It produces polished charts and graphics, offers a broad assortment of statistical procedures and tests, and can import data in multiple formats. Its functionality can be extended with community and developer modules for reporting, modeling, and advanced analyses, plus utilities for cleaning and reshaping datasets. It’s well suited to personal or small-scale projects, business analytics, and academic research or teaching. An alternative listed is SHAREit, though it is primarily a file-transfer utility rather than a statistics package and may not meet statistical needs.

Tinn-R: Editor - GUI for R Language and Environment

R is a programming language and runtime designed for statistical analysis and data visualization, drawing on ideas from the S language and available as an open-source project. It’s used for hypothesis testing, clustering and classification, linear and nonlinear modeling, time-series analysis and many custom statistical computations, and it produces publication-quality charts with support for mathematical notation and specialized plotting. Tinn-R is a free, open-source editor tailored to R that combines text-editing and IDE features to simplify writing, running and organizing code. It offers an integrated object browser, syntax highlighting, macro recording and an extensible auto-completion system; direct integration with R runtimes and support for literate programming workflows; conversion and output to LaTeX and other document formats; multilingual spell checking and powerful search-and-replace; easy sending of code or selections to the interpreter; and project management tools. Its extensibility, lack of licensing costs, and combination of editing conveniences with direct control over R sessions make it a practical, lightweight choice for scripting, exploratory analysis and reproducible reporting.

Minitab

Minitab is a statistical analysis package used across industries that combines advanced analytics with an approachable interface. It helps gather, summarize and visualize data—from basic charts to advanced plots—and includes a step-by-step Assistant that guides analysis and interpretation. Core capabilities include hypothesis testing (t-tests, ANOVA, chi-square), process capability studies, and diagnostic/exploratory plots for spotting patterns and outliers. It’s best suited to teams that work regularly with analytics; support is available and a trial can help evaluate whether it fits your workflow. As a no-cost alternative, OpenStat provides many basic and intermediate statistical analyses and can be a good place to start before committing to paid software.

R-project

R is a programming environment for statistical computing and graphics that helps researchers organize, analyze, visualize, and reproduce data-driven work. It offers a vast ecosystem of packages for specialized analyses (including bioinformatics), strong support for modeling and machine learning, time-series and classical statistics, and publication-quality graphics with fine-grained control. Because it is open and extensible, users can inspect or extend functionality to fit specialized workflows and build reproducible pipelines and project-centered workspaces. This environment is best suited to advanced students and researchers with a solid grounding in statistics and some programming experience. Paired with an integrated development environment, it streamlines coding, debugging, and project organization, but it does require a learning investment and careful statistical practice to avoid misinterpretation.

Stata

Stata is a comprehensive statistical analysis and data science package that combines data management, statistical modeling, and integrated visualization to produce reproducible results and professional reports. It offers fine-grained control for cleaning and manipulating datasets, a wide range of statistical tools for aggregation and modeling, and built-in charting to turn data into presentable outputs. The software supports import/export of many data formats and database connectivity, includes a spreadsheet-style interface for quick edits, and provides full Unicode support. It is designed to scale to very large datasets and is commonly used in classroom settings, academic research, and professional analytic workflows where reproducibility, data integrity, and scalable performance are important.

Minitab Statistical Software 22

Minitab 22 is a statistical analytics package that combines an approachable interface with advanced statistical tools to help teams analyze data and draw reliable conclusions. It lowers the learning curve for applying analytics while supporting a wide range of techniques for diverse business and research needs. By simplifying complex analyses, Minitab 22 helps organizations turn raw data into actionable insight, support evidence-based decision making, and improve operational outcomes and efficiency.

G*Power

G*Power is a utility for statistical power calculations and sample-size planning that supports common test families (F, z, χ², t and several exact tests). It provides modular entry panels to specify tails, distributions, and parameters, and includes integrated effect-size calculators (e.g., f², Cohen’s d) with conventional small/medium/large guidance that feed directly into analyses. Analyses include a priori, post hoc, sensitivity, and compromise/criterion approaches; results are shown as numeric tables (critical values, noncentrality parameters, estimated power) and customizable graphical summaries (power curves and comparisons). Tables and figures can be exported for reports. The tool focuses strictly on planning and evaluating power from user-specified parameters and does not import raw data or perform primary model fitting.

RKWard

RKWard is a graphical environment for working with the R language that combines a point-and-click interface with support for script-based workflows, making it easier to run statistical analyses and generate reproducible code. It provides dialogs that build R code behind the scenes so users can perform complex procedures without writing every command manually while still having access to the underlying scripts. Key features include an intelligent editor with code completion, collapsible sections and syntax highlighting, a spreadsheet-style data grid for inspecting and editing datasets, and tools for importing common data formats with previews. The environment also offers live plot previews, a browsable session history of commands and outputs, package and object management tools, and extensibility via plugins to tailor functionality.

Report inappropriate content