sleep.

A university in Italy was doing research on the effect of sleep on programming performance. The question is, where do we draw the line? When is the difference in performance big enough that you can't say that it is due to chance? Also, can't we explain the effect with gpa?

The Problem Summary The Plan Calculating Differences Histograms Drawing the Line Counting the Effect That GPA Though Wrapping Up

Prev Video

Next Video

Episode Notes

Here's the code we wrote to prepare for the gpa stats.

agg = (df
 .assign(gpa=lambda d: d['gpa'] < d['gpa'].mean())
 .groupby('gpa')
 .agg(mean_unit_tests=('passed_unit_tests', np.mean),
      mean_asserts=('passed_asserts', np.mean),
      mean_user_stories=('tackled_user_stories', np.mean))).T

effect_dict = dict(agg[False] - agg[True])
effect_dict

This is where we calculate the numbers exactly.

df_diff.assign(limit=lambda d: d['diff_unit_tests'] < 0.1948)['limit'].mean()
df_diff.assign(limit=lambda d: d['diff_asserts'] < 0.2922)['limit'].mean()
df_diff.assign(limit=lambda d: d['diff_user_stories'] < 0.0584)['limit'].mean()

Feedback? See an issue? Feel free to mention it here.

If you want to be kept up to date, consider getting the newsletter.