Abstract
The programming features of Mathematica allow one to augment this symbolic computing package with a variety of data analysis tools. Shown here are brief programs for kernel density estimation, robust regression, and bootstrap resampling. The programs take advantage of the numerous functions that are built into Mathematica, particularly those for graphics and iterative calculations. The illustrative analysis of the Duncan occupational status data includes surface plots of a quadratic regression surface and shows how to save, combine, and overlay graphics. In addition, the simulated data analysis session exploits the symbolic algebra capabilities of Mathematica to obtain the optimal smoothing parameter for a kernel density.
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