Free E-Learning Course. Learn how to use SAS/STAT software with this free e-learning course, Statistics 1: Introduction to ANOVA, Regression and Logistic Regression. This introductory SAS/STAT course is a prerequisite for several courses in our statistical analysis curriculum.
We have already explained how Microsoft Excel can be used as a basic statistical analysis software. The first step in the process requires turning on the Statistical Analysis feature, after which you can perform linear regression, ANOVA and much more.
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Unfortunately, for a more serious analysis users need specialized software such as SPSS, Eviews or Stata. These programs are expensive and not everyone can afford them. Luckily, there are plenty of free alternatives that can be used instead. Here we have created a list of the most popular free software for statistical analysis.
1) The R Project for Statistical Computing
R is by far the most widely used free statistical environment. It can be used for many different types of analysis. It has a large community and numerous packages are developed for it. Learning it will require a bit of programming knowledge, but there are plenty of tutorials and online courses available for that purpose. This is something we definitely recommend you learn, because it is slow-ly becoming the standard in many professional data analytics communities.
2) PSPP
This is a free alternative for SPSS, and a pretty mature project which can be used for regression analysis, non-parametric tests, T-tests, cluster analysis and much more. It supports over 1 billion variables.
3) Gretl
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Gretl is a free alternative to Eviews. It can be used for a wide range of econometric analyses, data series and regression.
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4) MicrOsiris
MicrOsiris is a lightweight freeware for performing all sorts of data analysis.
5) Regressit
A completely free add-in for Excel, Regressit can be used for multivariate descriptive data analysis and multiple linear regression analysis.
6) MacAnova
MacAnova is developed at the University of Minnesota and can be used for statistical analysis and matrix algebra.
7) GNU Octave
This tool presents an excellent alternative to Matlab. Not only can it be used for multiple numerical computations, it also has great data visualization capabilities.
8) Dmelt
This tool is a successor to a couple of other statistical environments. It can be used for mathematical analysis, visualization and much more.
JMP is the tool of choice for scientists, engineers and other data explorers in almost every industry and government sector. JMP combines dynamic data visualization with powerful statistics, in memory and on the desktop. Interactive and visual, JMP reveals insights that raw tables of numbers or static graphs tend to hide. The pro version of JMP offers all the tools in JMP plus advanced features for more sophisticated analyses, including predictive modeling and cross-validation techniques. Learn more about JMP Statistical Software
JMP, data analysis software for scientists and engineers, links dynamic data visualization with powerful statistics, on the desktop. Learn more about JMP Statistical Software
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JMP is the tool of choice for scientists, engineers and other data explorers in almost every industry and government sector. JMP combines dynamic data visualization with powerful statistics, in memory and on the desktop. Interactive and visual, JMP reveals insights that raw tables of numbers or static graphs tend to hide. The pro version of JMP offers all the tools in JMP plus advanced features for more sophisticated analyses, including predictive modeling and cross-validation techniques.