smoking.
It is easier that you might think to fool yourself with data. It is quantified so there is less bias right? This series of videos shows you an analysis using pandas that demonstrates why this might not be true.
Episode Notes
When we normalise against age, suddenly we see another pattern.
(clean_df
.assign(age=lambda d: np.round(d['age'] / 10) * 10)
.groupby(['smokes', 'age'])
.agg(p=('alive', np.mean))
.reset_index()
.pivot(index='age', columns='smokes', values='p')
.plot())
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