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Estimation of mean improvement

You will now estimate how big this current effect is. Compute the mean fractional improvement for being in a high-numbered lane versus a low-numbered lane, along with a 95% confidence interval of the mean.

Diese Übung ist Teil des Kurses

Case Studies in Statistical Thinking

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Anleitung zur Übung

  • Compute the mean fractional difference using np.mean(). The variable f from the last exercise is already in your namespace.
  • Draw 10,000 bootstrap replicates of the mean fractional difference using dcst.draw_bs_reps(). Store the result in a numpy array named bs_reps.
  • Compute the 95% confidence interval using np.percentile().
  • Hit 'Submit Answer' to print the mean fractional improvement and 95% confidence interval to the screen.

Interaktive Übung

Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.

# Compute the mean difference: f_mean
f_mean = ____

# Draw 10,000 bootstrap replicates: bs_reps
bs_reps = ____

# Compute 95% confidence interval: conf_int
conf_int = ____

# Print the result
print("""
mean frac. diff.: {0:.5f}
95% conf int of mean frac. diff.: [{1:.5f}, {2:.5f}]""".format(f_mean, *conf_int))
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