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🤝 Covariance

Covariance measures how two variables move together.

  • Positive: As Ice Cream sales go up, Sunburns go up.
  • Negative: As Winter Coat sales go up, Ice Cream sales go down.

🐍 Python Implementation​

We can compute the Covariance Matrix using numpy. The diagonal is the variance of each variable, and the off-diagonal is the covariance between them.

import numpy as np

# Ice cream sales vs Sunburns (They go up together)
ice_cream = [10, 20, 30, 40, 50]
sunburns =  [1,   3,  5,  7,  9]

# Calculate Covariance Matrix
cov_matrix = np.cov(ice_cream, sunburns)

print("Covariance Matrix:\n", cov_matrix)
# The positive number off the diagonal means they are positively related!