擅长:python、mysql、java
<pre><code>observation = [16, 22, 40, 43, 65, 75]
import numpy as np
import scipy.stats
def Q_Q_Prob(data):
n = len(data)
prob_level = []
for i in range(1,n+1):
prob_level.append(np.round((i-0.5)/n,5))
Standard_normal_quantiles = scipy.stats.norm.ppf(prob_level)
return Standard_normal_quantiles
print(Q_Q_Prob(observation))
</code></pre>
<p>这为书名为:Applied Multivariable中的示例提供了精确的结果
统计分析(RICHARD A.JOHNSON)<a href="https://i.stack.imgur.com/IxGQV.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/IxGQV.png" alt="see the example"/></a>,但没有给出所述示例的准确值。分享这个,因为这可能会给你一个想法</p>