Visualize the walk
The current walk depends on the previous one.
import numpy as np np.random.seed(123) random_walk =  # initial for x in range(100): # 100 walks step = random_walk[-1] # take the last step dice = np.random.randint(1,7) # from 1 to 6 if dice <= 2: step = max(0, step - 1) # prevent back to less than 0 elif dice <= 5: step += 1 else: step += np.random.randint(1,7) random_walk.append(step) import matplotlib.pyplot as plt plt.plot(random_walk) plt.show()
- Question: random walk go up/down (of tails) but what is the chance to go up to 65, for example?
- Idea: run 100 times the algorithm of random walk to get the last “tails” and then see the distribution of this final tail and guest the chance. Using histogram to visualize the distribution.