albertyumol
/ fb_4.ipynb
Created
May 20, 2020 01:25
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albertyumol
/ fb_3.ipynb
Created
May 20, 2020 00:39
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albertyumol
/ fb_2.ipynb
Created
May 20, 2020 00:05
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albertyumol
/ fb_1.ipynb
Created
May 19, 2020 23:45
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albertyumol
/ confidence_intervals.ipynb
Created
October 25, 2019 01:25
Sample problem for demonstrating confidence intervals in Python.
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albertyumol
/ hypothesys_testing.ipynb
Created
October 25, 2019 01:22
Saple problem for hypothesis testing in Python.
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| import numpy as np | |
| import matplotlib.pyplot as plt | |
| def normal_pdf(x, mu=0, sigma=1): | |
| sqrt_two_pi = np.sqrt(2*np.pi) | |
| return (np.exp(-(x-mu)**2/2/sigma**2)/(sqrt_two_pi*sigma)) | |
| xs = [x / 10.0 for x in range(-50, 50)] | |
| plt.plot(xs, [normal_pdf(x, sigma=1) for x in xs], '-', label='$\mu=0$, $\sigma=1$') | |
| plt.plot(xs, [normal_pdf(x, sigma=2) for x in xs], '--', label='$\mu=0$, $\sigma=2$') | |
| plt.plot(xs, [normal_pdf(x, sigma=0.5) for x in xs], ':', label='$\mu=0$, $\sigma=0.5$') |
albertyumol
/ boy_or_girl.py
Created
October 24, 2019 05:47
Calculating conditional probabilities in Python.
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| import random | |
| def random_kid(): | |
| return random.choice(['boy','girl']) | |
| both_girls = 0 | |
| older_girl = 0 | |
| either_girl = 0 | |
| random.seed(7) | |
| for i in range(1000000): |
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| #Provided that x and y have the same length. | |
| import numpy as np | |
| def standard_deviation(x): | |
| x_bar = np.mean(x) | |
| N = len(x) | |
| deviation_mean = [x_i - x_bar for x_i in x] | |
| return np.sqrt(np.dot(deviation_mean, deviation_mean) / N) | |
| def covariance(x, y): | |
| N = len(x) |
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| #Provided that x and y have the same length. | |
| import numpy as np | |
| def covariance(x, y): | |
| N = len(x) | |
| x_bar = np.mean(x) | |
| y_bar = np.mean(y) | |
| deviation_mean_x = [x_i - x_bar for x_i in x] | |
| deviation_mean_y = [y_i - y_bar for y_i in y] | |
| return np.dot(deviation_mean_x, deviation_mean_y) / N |
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