Session 6: Uncertainty & Stats – Probabilistic Thinking

Discuss

Real aero has variability (wind, errors). "Designers communicate uncertainty—like in your capstone."

Code

import numpy as np
import matplotlib.pyplot as plt

data = np.random.normal(0, 1, 1000)  # Simulated wind noise
plt.hist(data, bins=30)
plt.title('Uncertainty: Normal Distribution for Wind')
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.grid(True)
plt.show()

Add random noise (numpy.random) to simulations; compute means/variances for reliability.

Excite

Run Monte Carlo sims—see distribution of landing spots. "This is gamified risk!"

Homework

Analyze limitations (e.g., "What if wind is extreme?").