August 2015
Intermediate to advanced
272 pages
5h 46m
Japanese
Content preview from Think Stats 第2版 ―プログラマのための統計入門
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50
4 章 累積分布関数
4.3
累積分布関数（
CDF
）
パーセンタイル値とパーセンタイル順位を理解したので、累積分布関数（
cumulative
distribution function
、
CDF
）に取り掛かれます。
CDF
は、値を、パーセンタイル順
位に対応付ける関数です。
CDF
は、分布に現れる任意の値
x
の関数になります。ある
x
について
CDF(x)
を
評価することは、分布中で
x
以下の値の割合を計算することです。
この計算をシーケンス
t
と値
x
を引数として受け取る関数として書くと次のように
なります。
def EvalCdf(t, x):
count = 0.0
for value in t:
if value <= x:
count += 1
prob = count / len(t)
return prob
この関数は
PercentileRank
と、結果が
0
〜
100
の範囲のパーセンタイル順位では
なく
0
〜
1
の範囲の確率であるということを除いて、ほぼ同一です。
例として、値
[1, 2, 2, 3, 5]
の標本を考えましょう。
CDF
は次のようになります。
CDF(0)
＝
0
CDF(1)
＝
0.2
CDF(2)
＝
0.6
CDF(3)
＝
0.8
CDF(4)
＝
0.8
CDF(5)
＝
1
標本に現れる値だけでなく、どのような
x
に対しても、
CDF
は計算できます。も
し
x
が標本中の最小値より小さかったなら、
CDF(x)
は
0
になります。もし
x
が標本
中の最大値よりも大きかったら、
CDF(x)
は
1
になります。
図
4-2
は、
CDF
のグラフ表示です。標本の ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.