Our curated compilation covers all categories of software. ![]() Read our complete collection of recommended free and open source software. Statistical package for both Bayesian and Frequentist statistical methods Solves the data analysis challenges of high-energy physicsįree replacement of the proprietary program, SPSSĮxtremely user-friendly statistics, analysis and reporting package Regression, Econometric and Time-Series Library Statistical Analysis ToolsĮnvironment for statistical computing and graphics For each title we have compiled its own portal page, a full description with an in-depth analysis of its features, a screenshot of the software in action, together with links to relevant resources. Let’s explore the 8 statistical analysis tools at hand. Their presentation are examples to developers of how to design and implement intuitive software. If you are looking for a really easy-to-use package, look no further than PSPP and SOFA Statistics. It consists of a language together with a run-time environment with a debugger, graphics, access to system functions, and scripting. We give our strongest recommendation to R, an open source programming language and software environment for statistical computing and graphics. ![]() Only free and open source software is included. Here’s our verdict captured in a legendary LinuxLinks chart. ![]() This type of software helps to summarize data in a shorter form, and helps scientists understand a concept or representation and make possible predictions based on this understanding. The purpose of this article is to identify software for performing statistical analysis. Linux is particularly strong in the field of open source statistical software.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |