Software Title

Software Description

GAUSS

The GAUSS Mathematical and Statistical System is a fast matrix programming language widely used by scientists, engineers, statisticians, biometricians, econometricians, and financial analysts. The GAUSS system is ideally designed for computationally intensive tasks.

Maple

Maple is a comprehensive computer system for advanced symbolic mathematics. It includes facilities for interactive algebra, calculus, discrete mathematics, graphics, numerical computation and many other areas of mathematics. It also provides a unique environment for rapid development of mathematical programs using its vast library of built-in functions and operations.

Mathematica

Mathematica provides a fully integrated environment for technical computing. The usage of Mathematica is not only in the physical sciences, engineering and mathematics but also in the social science and commerce. It is also an important tool in computer science and software development.

Matlab

Matlab is a high performance language for technical computing. Computation, visualization, and programming are integrated in an easy-to-use environment. Matlab can be used for mathematics, modeling, simulation, data analysis, visualization, scientific and engineering graphics.

Octave

GNU Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command line interface for solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with Matlab. It may also be used as a batch-oriented language.

R

R is 'GNU S', a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modeling, statistical tests, time series analysis, classification, clustering, etc.

SAS

The SAS System is a powerful programming language and a collection of ready-to-use programs called procedures. It has data access, data management, data presentation, and data analysis capabilities. Its roots are in academia, particularly statistical analysis, but SAS has broadened its applications to include dozens of tools from data entry products to a scalable performance data server product. The power of the SAS System comes from the integration of all of the SAS applications so they work together. Additionally, the SAS System is portable, you can easily move SAS applications across platforms. Finally, SAS has flexible user interfaces; this means if you would rather not learn the SAS programming language you can use the SAS user interface products for a menu-driven, task-oriented, and point-and-click environment.

SAVAS

SAVAS is an application designed to translate data files from SAS datasets into Stata datasets or Stata datasets to SAS datasets.

S-Plus

S-Plus is a programming environment for data analysis. Highlights of S-Plus are its graphic capabilities, its orientation to exploratory data analysis and data mining, and the inclusion of many non parametric statistical methods. The main disadvantage of S-Plus is the steep learning curve to learn the programming language. S-Plus is based on the S language, developed at Bell Laboratories by statistician John M. Chambers.

Stata

Stata is a complete, integrated statistical package for data analysis, data management, and graphics. It covers a wide range of statistical techniques and is programmable. Stata includes a variety of routines to analyze complex data and is a general purpose statistical package with good graphics capabilities and a graphic editor. Among the highlights of Stata are that it is relatively easy to learn for beginners. A fast and complete matrix programming language is an integral part of Stata.

SUDAAN

SUDAAN is a program designed to analyze survey data while accounting for complex sampling procedures. The SUDAAN statistical analysis system has procedures for analyzing clustered data from both complex sample surveys and experimental studies in clinical trials, toxicology, and epidemiology. SUDAAN describes itself as "specifically designed for the analysis of clustered data arising in many applications, including complex sample surveys, randomized experiments, and epidemiological studies. Complex sample survey designs often include stratification, multistage cluster sampling, and unequal probabilities of selection. These survey designs reduce the cost of data collection but in exchange complicate the statistical analyzes, since the observations are no longer independent and identically distributed (iid). Unlike standard statistical packages, SUDAAN is specifically designed to handle non-iid observations drawn from finite populations."