 # Normal Distribution in Python

Jul 4th, 2022
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1. import numpy as np
2. import matplotlib.pyplot as plt
3. import seaborn as sns
4. from scipy.stats import norm
5.
6. # Perfume bottles are filled with the average volume of 150cc and the standard deviation of 2cc. What percent of bottles will have the # volume more than 153cc?
7. mu = 150
8. std = 2
9. 1 - norm.cdf(153, mu, std)
10.
11. # Perfume bottles are filled with the average volume of 150cc and the standard deviation of 2cc. What percent of bottles will have the # volume between 148 and 152cc?
12. left_side = norm.cdf(148, mu, std)
13. right_side = 1 - norm.cdf(152, mu, std)
14. result = 1 - left_side - right_side
15. result
16.
17. # What percent of bottles will have the volume exactly 150cc?
18. result = norm.pdf(150,mu,std)
19. result
20.
21. # What percent of bottles will have the volume less than 150cc?
22. norm.cdf(150,mu,std)
23.
24. # Visualization
25. x_ax = np.linspace(144,156,130)
26. y_ax = norm.pdf(x_ax, mu,std)
27. sns.lineplot(x=x_ax, y = y_ax)
28. plt.axvline(153, color = 'red')
29. plt.show()