Open Source Windows Statistics Software
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Statistics Software for Windows
View 34 business solutionsBrowse free open source Statistics software and projects for Windows below. Use the toggles on the left to filter open source Statistics software by OS, license, language, programming language, and project status.
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Secure File Transfer for Windows with Cerberus by RedwoodCerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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gretl
A cross-platform statistical package for econometric analysis
gretl is a cross-platform software package for econometric analysis, written in the C programming language. -
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Practically Random
statistical tests & psuedo- random number generators (RNGs, PRNGs)
Randon number generation & testing. The best suite of statistical tests for fast PRNGs anywhere. Multithreaded for speed, command line tools for automation, no upper limit on data size. Also, a variety of C++ pseudo-random number generators with well designed interfaces aimed at practical uses, not just research. -
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R portable configures R to work with the PortableApps framework, so that R can be ran from a thumb drive or portable hard drive without leaving artifacts on the computer.
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SOFA is a statistics, analysis, and reporting program with an emphasis on ease of use, learn as you go, and beautiful output.
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Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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seaborn
Statistical data visualization in Python
Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Seaborn helps you explore and understand your data. Its plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mapping and statistical aggregation to produce informative plots. Its dataset-oriented, declarative API lets you focus on what the different elements of your plots mean, rather than on the details of how to draw them. Behind the scenes, seaborn uses matplotlib to draw its plots. For interactive work, it’s recommended to use a Jupyter/IPython interface in matplotlib mode, or else you’ll have to call matplotlib.pyplot.show() when you want to see the plot. -
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LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
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R packages (maintained by YJLEE)
R packages for PK/PD modeling , BE/BA, drug stability, ivivc, etc.
These R packages are developed for data analysis of PK/PD modeling & simulation, bioequivalence/bioavailability (BE/BA), drug stability, in-vitro and in-vivo correlation (ivivc), as well as therapeutic drug monitoring (TDM). -
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MAGeCK
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) is a computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology. For instructions and documentations, please refer to the wiki page. MAGeCK is developed by Wei Li and Han Xu from Dr. Xiaole Shirley Liu's lab at Dana-Farber Cancer Institute/Harvard School of Public Health, and is maintained by Wei Li lab at Children's National Medical Center. We thank the support from Claudia Adams Barr Program in Innovative Basic Cancer Research and NIH/NHGRI to develop MAGeCK. -
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AlphaPlot
Interactive scientific graphing and data analysis software.
Alpha Plot can generate different types of 2D and 3D plots (such as line, scatter, bar, pie, and surface plots) from data that is either imported from ASCII files, entered by hand, or calculated using formulas. The data is held in spreadsheets which are referred to as tables with column-based data (typically X and Y values for 2D plots) or matrices (for 3D plots). The spreadsheets as well as graphs and note windows are gathered in a project and can be organized using folders. The built-in analysis operations include column/row statistics, (de)convolution, FFT and FFT-based filters. Scripting Console support in-place evaluation of mathematical expressions and scrtipting interface to ECMAScript like dynamic scripting language(java script). The GUI of the application uses the Qt toolkit. Periodic test builds are available here http://alphaplot.sourceforge.net/test-build.html -
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UnBBayes
Framework & GUI for Bayes Nets and other probabilistic models.
UnBBayes is a probabilistic network framework written in Java. It has both a GUI and an API with inference, sampling, learning and evaluation. It supports Bayesian networks, influence diagrams, MSBN, OOBN, HBN, MEBN/PR-OWL, PRM, structure, parameter and incremental learning. Please, visit our wiki (https://sourceforge.net/p/unbbayes/wiki/Home/) for more information. Check out the license section (https://sourceforge.net/p/unbbayes/wiki/License/) for our licensing policy. -
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Epidat
Statistical data analysis
Programa multiplataforma de libre distribución para el análisis estadístico y epidemiológico de datos. Free distribution cross-platform program for statistical and epidemiological analysis of data. Sitio web: http://www.sergas.es/Saude-publica/EPIDAT Souceforge: https://sourceforge.net/projects/epidat/ Wikipedia: https://es.wikipedia.org/wiki/Epidat -
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This material enables IBM SPSS Statistics users to run code written in the R language inside Statistics. Additional free items for R in Statistics and other materials are available from the SPSS Community at www.ibm.com/developerworks/spssdevcentral
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FieldTrip
The MATLAB toolbox for MEG, EEG and iEEG analysis
FieldTrip is the MATLAB software toolbox for MEG, EEG and iEEG analysis, which is released free of charge as open source software under the GNU general public license. FieldTrip is developed by members and collaborators of the Donders Institute for Brain, Cognition, and Behaviour at Radboud University, Nijmegen, the Netherlands. The toolbox offers advanced analysis methods of MEG, EEG, and invasive electrophysiological data, such as time-frequency analysis, source reconstruction using dipoles, distributed sources and beamformers and non-parametric statistical testing. It supports the data formats of all major MEG systems (CTF, Neuromag/Elekta/Megin, BTi/4D, Yokogawa/Ricoh, FieldLine) and of most popular EEG systems, and new formats can be added easily. FieldTrip contains high-level functions that you can use to construct your own analysis protocols in MATLAB. Furthermore, it easily allows methods researchers to incorporate new methods for EEG/MEG analysis. -
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PyMC
Bayesian Modeling and Probabilistic Programming in Python
PyMC is a Python library for probabilistic programming focused on Bayesian statistical modeling and machine learning. Built on top of computational tools like Aesara and NumPy, PyMC allows users to define models using intuitive syntax and perform inference using MCMC, variational inference, and other advanced algorithms. It’s widely used in scientific research, data science, and decision modeling. -
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Statistics
Detects usage of unsafe Rust in a Rust crate and its dependencies
A tool that lists statistics related to the usage of unsafe Rust code in a Rust crate and all its dependencies. -
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rethinking
Statistical Rethinking course and book package
This R package accompanies Richard McElreath’s Statistical Rethinking (2nd edition), offering utilities to fit and compare Bayesian models using both MAP estimation (quap) and Hamiltonian Monte Carlo via RStan (ulam). It supports specifying models via explicit distributional assumptions, providing flexibility for advanced statistical workflows. -
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KinetDS is a software for curve fitting particularly designed for kinetic (mechanistic and empirical) description of a substance dissolution from solid state. It was primarily designed for handling pharmaceutical dissolution tests
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PhEq_bootstrap
FDA's f2 computation with bootstrap technique
This program was developed as a help in establishing pharmaceutical equivalence by use of FDA f2 coefficient. It was designed to help with f2 computation in cases when intra- and inter-batch variability is large, namely RSD>10%. The use of statistical bootstrap technique allows to implement confidence interval (CI) into the f2 coefficients resulting in overcoming of their major drawback in the original metrics. The algorithm provides possible “worst case scenario” of f2 values, thus supporting claim about pharmaceutical equivalence. The target users are researchers from industry and academia dealing with pharmaceutical equivalence problem. The software is Open Source. It was developed in Lazarus environment, therefore source code is available in ObjectPascal. -
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Statcato is a Java software application for elementary statistics. Its features include data and graph generation, probability distributions, descriptive statistics, confidence intervals, hypothesis tests, correlation, regression, and analysis of var
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bootf2BCA
computing f2 bootstrap CI BCA
Computing similarity factor (f2) bootstrap bias corrected and accelerated confidence interval -
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QPNet
Synchronous Petri Nets' emulator
QPNet (Quick Petri Net) is a fast Petri Nets' emulator, created by students of Moscow State Technical University of Radio Engineering, Electronics and Automation. It brings benefits for the educational process, while being under further development and extension. QPNet это быстрый эмулятор сетей Петри, созданный студентами МИРЭА. Он применяется в учебном процессе, а так же продолжает разрабатываться и эволюционировать. -
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STK
a Small (Matlab/Octave) Toolbox for Kriging
The STK is a (not so) Small Toolbox for Kriging. Its primary focus in on the interpolation / regression technique known as kriging, which is very closely related to Splines and Radial Basis Functions, and can be interpreted as a non-parametric Bayesian method using a Gaussian Process (GP) prior. The STK also provides tools for the sequential and non-sequential design of experiments. Even though it is, currently, mostly geared towards the Design and Analysis of Computer Experiments (DACE), the STK can be useful for other applications areas (such as Geostatistics, Machine Learning, Non-parametric Regression, etc.). -
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PMM-Lab
Predictive Microbial Modeling plug-in for KNIME
PMM-Lab is an open-source extension to the Konstanz Information Miner (KNIME). It consists of three components: • a library of KNIME nodes (called PMM-Lab), • a library of “standard” workflows • an HSQL database.to store experimental data and microbial models. Altogether these components are designed to ease and standardize the statistical analysis of experimental microbial data and the development of predictive microbial models (PMM). Users can apply PMM-Lab to proprietary or public data and create bacterial growth / survival / inactivation models. The framework can easily be extended to other model types, e.g. growth/no-growth boundary models. PMM-Lab has been initiated and provided by the Federal Institute for Risk Assessment - BfR (Berlin, Germany). The software is in Beta status. Before using the software you have to read and accept the license and disclaimer (https://sourceforge.net/p/pmmlab/wiki/Disclaimer/). If you do not agree, do not use this software. -
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Statistics101 - Resampling Statistics
Use simulation to perform statistical analyses.
Statistics101 is an Integrated Development Environment (IDE) that uses a simple, powerful language called “Resampling Stats” to develop Monte Carlo programs to analyze and solve statistical problems. The original Resampling Stats language and computer program were developed by Dr. Julian Simon (https://www.juliansimon.com/) and Peter Bruce (https://www.scientificamerican.com/author/peter-bruce/) as a new way to teach Statistics to social science students. Of course, social science students aren't the only ones who can benefit. Anyone who wants to learn statistics will find that the resampling approach helps in understanding statistical concepts from the simplest to the most difficult. In addition, professionals who want to use resampling, bootstrapping, or Monte Carlo simulations will find Statistics101 helpful. More information at https://statistics101.sourceforge.io/ -
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FRUITS
Food Reconstruction Using Isotopic Transferred Signals
Description IMPORTANT NOTICE: The current release of FRUITS (FRUITS 3.1) will be the last as a Windows installer. This version is the closest to the soon to be released R-based ReSources package as part of the IsoMemo initiative. FRUITS is a Bayesian mixing model for diet reconstruction using isotopic data.
