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Normalizing metrics

We previously saw that there was not a significant difference between the brain volumes of elderly individuals with and without Alzheimer's Disease.

But could a correlated measure, such as "skull volume" be masking the differences?

For this exercise, calculate a new test statistic for the comparison of brain volume between groups, after adjusting for the subject's skull size.


Using results.statistic and results.pvalue as your guide, answer the question: Is there strong evidence that Alzheimer's Disease is marked by smaller brain size, relative to skull size?

This exercise is part of the course

Biomedical Image Analysis in Python

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import independent two-sample t-test
____

# Divide `df.brain_vol` by `df.skull_vol`
df['adj_brain_vol'] = ____

# Select brain measures by Alzheimers group
brain_alz = df.loc[df.alzheimers == ____, 'adj_brain_vol']
brain_typ = df.loc[____, 'adj_brain_vol']

# Evaluate null hypothesis
results = ____
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