機率與統計: 練習

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

• github

靠杯！！！　要炸掉拉～　ＸＤＤ

量好多　ＸＤＤ

Exercise 4-2

小圓籃球細胞！！！　

• github

Exercise 5-2

• github

Exercise 7-1

• github

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

• github