Quantitative Data Analysis Tools:

  • CADStat is a menu-driven package of several data visualization and statistical methods. It is based on a Java Graphical User Interface to R. Methods in this package include: scatterplots, box plots, correlation analysis, linear regression, quantile regression, conditional probability analysis, and tools for predicting environmental conditions from biological observations.
  • KNIME, the Konstanz Information Miner, is a user-friendly, coherent open source data analytics, reporting and integration platform. KNIME integrates various components for machine learning and data mining through its modular data pipelining concept.
  • jHepWork is a free data-analysis framework for scientists, engineers and students written in Java. The program can be used everywhere where an analysis of large numerical data volumes, data mining, statistical data analysis and mathematics are essential. The program can be used in natural sciences, engineering, modeling and analysis of financial markets. It uses Jython, the Python language for the Java platform in order to call Java numerical and visualization libraries, which brings more power and simplicity for scientific computing.
  • Minitab is the leading provider of software for statistics education and Lean, Six Sigma, and quality improvement projects. [Not free]
  • Microsoft Excel
  • PAW, Physics Analysis Workstation, is conceived as an instrument to assist physicists in the analysis and presentation of their data. It provides interactive graphical presentation and statistical or mathematical analysis, working on objects familiar to physicists like histograms, event files (Ntuples), vectors, etc.
  • PSPP is a program for statistical analysis of sampled data. It is a Free replacement for the proprietary program SPSS, and appears very similar to it with a few exceptions.
  • Q is a new data analysis program from Australia-based Numbers International that is designed to allow researchers to reveal hidden depths in their survey data using the power of statistical testing and modeling but without expecting researchers to become advanced statisticians. [Not free]
  • R is a free software environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.
  • ROOT is an object-oriented program and library developed by CERN (The European Organization for Nuclear Research). It was originally designed for particle physics data analysis and contains several features specific to this field, but it is also used in other applications such as astronomy and data mining.
  • SPSS (originally, Statistical Package for the Social Sciences) was released in its first version in 1968 after being developed by Norman H. Nie and C. Hadlai Hull. SPSS is among the most widely used programs for statistical analysis in social science. It is “SPSS: An IBM Company” since July 2009. [not free]

Resources:

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