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?
Diese Übung ist Teil des Kurses
Biomedical Image Analysis in Python
Interaktive Übung
Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.
# 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 = ____