Top 7 Most Popular Regression Softwares | May 2024

1. GetNexrad

GetNexrad.exe is a tool used to view NOAA WSR-88D Nexrad doppler radar images and compute point and area average rainfall and to generate the basin point file used by GetRealtime.exe for automating computaion of a basin average rainfall time series in real time....... TpSort Score | 197,000,000

2. PAST - PAlaeontological STatistics

PAST is a free, easy-to-use data analysis package originally aimed at paleontology but now also popular in many other fields. It includes common statistical, plotting and modelling functions....... TpSort Score | 30,400,000

3. Webinject

WebInject is a free tool for automated testing of web applications and web services. It can be used to test individual system components with HTTP interfaces, as a test harness to create a suite of functional and regression tests, or for service-level monitoring....... TpSort Score | 28,300,000

4. Variables

Variables is a highly graphical and intuitive data analysis package. Explore your data, create sophisticated models and prepare stunning visualizations, all with your fingertips.Variables provides: - descriptive analysis of both numerical and categorical variables- visualizations of the distribution of a single variable, like histogram and kernel density estimates- measuring association...... TpSort Score | 15,800,000

5. Wizard Pro

Wizard is a new Mac app that makes data analysis easier than ever. No programming, no typing — just click and explore. Wizard includes a full set of tools for doing professional research, yet its friendly interface makes statistics accessible to beginners. Within minutes of opening Wizard for the first...... TpSort Score | 9,190,000

6. Sigma Magic

Sigma Magic Software - Excel Data Analysis Software for Lean, Six Sigma, DMAIC, DFSS, Statistical Analysis, Graphical Analysis, Monte Carlo Simulations...... TpSort Score | 993,000

7. KEEL

KEEL is an open source (GPLv3) Java software tool to assess evolutionary algorithms for Data Mining problems including regression, classification, clustering, pattern mining and so on. It contains a big collection of classical knowledge extraction algorithms, preprocessing techniques (training set selection, feature selection, discretization, imputation methods for missing values, etc.),...... TpSort Score | 791,000