This software provides CSV import/export, descriptive statistics, hypothesis tests, probability distributions, chi-square and T-tests, linear regression and correlation, random number generators, and ANOVA analysis.
Developed by numerical experts with a proven track record in the financial industry, the object-oriented library is designed to be simple and intuitive for developers at all levels, with an easy-to-use object model that lets you analyze your data quickly and efficiently.
Using the library, you can import data objects such as ADO.NET data tables, and a powerful CSV reader is also included, allowing you to work with existing data files. You can also easily bind to virtually any data source, including standard data objects, arrays, lists or your own object model.
With Statsar, you can sort and reorder data based on complex criteria, and multiple data filters are included, allowing you to remove unwanted or missing values with ease. A range of descriptive statistics are also available, including count, sum, min, max, mean, mode, median, standard deviation and variance.
The library includes multiple probability distributions, including binomial, negative binomial, Laplace, Poisson, chi-squared, beta, gamma, F, normal, lognormal and student's T. You'll also find random number generators, including Mersenne twister pseudorandom numbers.
Other features of Statsar include linear regression with least squares minimization, T-test, Z-test, and Kolmogorov-Smirnov test (including one sample and two sample testing), as well as analysis of variance (ANOVA) including RANOVA and one-way and two-way testing.
Getting started with Statsar is easy, with a download that includes a user guide, reference manual and over 25 examples in C# and VB.NET. So if you're looking for a comprehensive statistics library for your .NET applications, Statsar could be just what you need.
Version 1.0.1: Support for new quantile types (weighted averages, closest observation, empirical distribution, empirical distribution averaged) and weighted percentiles.