Wolfram Research

Experimental Data Analyst 1.3

Fitting, Visualization, and Error Analysis with the Power of Mathematica

Experimental Data Analyst Mathematica 9 compatible From extensive data fitting capabilities to data visualization and transformation, Experimental Data Analyst provides you with an impressive set of detailed programs and packages that help you get the most out of your experimental data. A wide array of examples that include real experimental data quickly gets you up and running on your own projects and helps you harness the power and flexibility of Mathematica.

Extensive error-analysis capabilities in Experimental Data Analyst easily handle errors in both coordinates of the data, obtain estimated errors in the fit parameters, and examine graphical information about the fit, including residuals of the fit.

Experimental Data Analyst allows you to fit data to linear or arbitrary models. You can fit data to lines or curves when one or more of the data points may be "wild" and the least-squares technique cannot be used. For advanced problems, it's easy to customize the behavior of the fitting routines by selecting from numerous options. For less complex cases, you can simply rely on the defaults for quick, accurate solutions.

Various data transformation techniques such as data smoothing and noise elimination as well as routines that automatically propagate errors of precision are available.

Impressive graphics capabilities provide a rich environment for visualizing your experimental data. An extension of Mathematica's function ListPlot visualizes errors in your data coordinates with error bars. The distribution of your data values can be viewed pictorially using histograms or box plots. You can fully control the display based on the data, the number of bins, the min, and the max.

The package comes with electronic documentation, which is fully integrated with the Mathematica Help Browser.

Product Support

Experimental Data Analyst is developed and supported by the University of Toronto Department of Physics.

University of Toronto
Department of Physics
60 St. George Street
Toronto, ON M5S 1A7
email: harrison@physics.utoronto.ca

Experimental Data Analyst 1.3 requires Mathematica 6, 7, 8, or 9 and is available for Windows, Mac OS X, and Linux.