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可以觀看 github

畫 CDF

import scipy.stats as stats
import matplotlib.pyplot as plt
import numpy as np

# 請查看 P(X <= -1),X服從標準常態分佈:
norm_cdf = stats.norm.cdf
print("P(X <= -1) = ", norm_cdf(-1, loc = 0, scale = 1))

# 請畫出標準常態分佈的累積機率函數(CDF),範圍從-3至3:
x = np.linspace(-3, 3, 1000)
norm_cdf = stats.norm.cdf

plt.plot(x, norm_cdf(x, loc = 0, scale = 1))
plt.arrow(-1, 0, 0, norm_cdf(-1, loc = 0, scale = 1), head_width=0.02, width=0.005, head_length=0.02, color='r')
plt.arrow(-1, norm_cdf(-1, loc = 0, scale = 1), -3, 0, head_width=0.02, width=0.005, head_length=0.02, color='g')
plt.show()

好不浪費時間~ 繼續讀書哈哈阿 自己去看 github

Exercise 4-1

靠杯!!! 要炸掉拉~ XDD

量好多 XDD

Exercise 4-2

小圓籃球細胞!!! 

Exercise 5-2

Exercise 7-1

不管了,反正我都有練到沒丟上 blog 的就自己去看 github XDD

Exercise 8-1: 資料轉換