Identifying potential confounds
Once measures have been extracted, double-check for dependencies within your data. This is especially true if any image parameters (sampling rate, field of view) might differ between subjects, or you pull multiple measures from a single image.
For the final exercises, we have combined demographic and brain volume measures into a pandas DataFrame (df).
First, you will explore the table and available variables. Then, you will check for correlations between the data.
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<Kurs>Biomedical Image Analysis in Python</Kurs>Interaktive praktische Übung
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# Print random sample of rows
print(____)