1. Learn
  2. /
  3. Courses
  4. /
  5. Sampling in Python

Exercise

Understanding random seeds

While random numbers are important for many analyses, they create a problem: the results you get can vary slightly. This can cause awkward conversations with your boss when your script for calculating the sales forecast gives different answers each time.

Setting the seed for numpy's random number generator helps avoid such problems by making the random number generation reproducible.

Instructions 1/3

undefined XP
    1
    2
    3

Question

Which statement about x and y is true?

import numpy as np
np.random.seed(123)
x = np.random.normal(size=5)
y = np.random.normal(size=5)

Possible answers