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Gist 9557217

✓ Published0🌍 Public
Aakeshavan
Last edited Mar 17, 2014
Created on Mar 14, 2014

This example simulates brain-volume measurements for healthy controls and multiple-sclerosis patients across two scan protocols, using synthetic data generated with NumPy and Statsmodels. It shows how measurement noise and protocol-related biases affect the relationship between age, disability scores, and brain volume. The visualization displays the simulated distributions and calibration results, with matplotlib and prettyplotlib rendering static plots. The code relies on inline plotting via `%pylab` and custom utility functions for distribution and calibration analysis, though no interactive or WebGL output is present in the provided notebook cells.

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