1. Learn
    2. /
  2. Courses
    3. /
  3. Foundations of Inference in Python

Exercise

Bonferonni-Holm correction

You've seen that comparing many different datasets, even randomly generated ones, can result in "statistically significant relationships" that are anything but! One way around this is to apply a correction to the alpha of your confidence level. In this exercise you'll explore why you should apply this correction and how to do so.

The 1000 p-values you calculated in the previous exercise have been loaded for you in a NumPy array p_values, as has the package NumPy as np.

Instructions 1/3

undefined XP
    1
    2
    3
  • Compute the Bonferonni-corrected value of alpha = 5%.
  • Print out how many of the p-values were less than this corrected cutoff.