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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54
4 章 累積分布関数
4.6
パーセンタイル派生統計量
CDF
を一旦計算すれば、パーセンタイル値とパーセンタイル順位の計算は容易で
す。
Cdf
クラスには、次の
2
つのメソッドがあります。
PercentileRank(x)
値
x
について、パーセンタイル順位、
100
・
CDF(x)
を計算する。
Percentile(p)
パーセンタイル順位
rank
について、対応する値
x
を計算する。
Value(p/100)
と
等価です。
Percentile
は、パーセンタイル派生要約統計量を計算するのに使えます。例えば、
50
位パーセンタイル値は、分布を半分に分割する値で、中央値（
median
）と呼ばれ
ます。平均値同様、中央値は、分布の中心傾向の尺度です。
実際のところ、「中央値」には、それぞれ特性が異なる複数の定義があります。
Percentile(50)
は、単純で計算が効率的です。
パーセンタイル派生統計量のもう
1
つは、四分位範囲（
interquartile range
、
IQR
）です。これは分布の広がり方の尺度です。
IQR
は、
75
位パーセンタイル値と
25
位パーセンタイル値との差です。
一般的に、パーセンタイル値は分布の形状の要約によく用いられます。例えば、収
入の分布は、「五分位数」でよく報じられます。すなわち、
20
位、
40
位、
60
位、
80
位パー
センタイル値に分けて示されます。他の分布では、「十分位数」に分けられるものが
あります。
CDF
において等間隔点で表現されるこのような統計量は、まとめて分位
数（
quantiles
）と呼ばれます ...
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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.