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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125
125
9.4 他の検定統計量
図
9-1
に結果を示します。
CDF
は、
0.83
で観察された差と交わります。これは、
p
値
0.17
の補数の値です。
同じ分析を出生時体重について行うと、計算した
p
値は
0
です。
1,000
回試みた後で、
シミュレーションは、観察された差の
0.12
ポンドほど大きな効果を生成することは
ありませんでした。したがって、
p
＜
0.001
という報告で、出生時体重の差は統計的
に有意だと結論します。
9.4
他の検定統計量
最適な検定統計量の選択は、どのような質問に答えるかに依存します。例えば、質
問が第一子について妊娠期間に差があるかというものなら、前節で行ったように平均
の差の絶対値を検定することに意味があります。
何らかの理由で、第一子の出産が遅れると考えるなら、差の絶対値を取るのではな
くて、次のような検定統計量を使います。
class DiffMeansOneSided(DiffMeansPermute):
def TestStatistic(self, data):
group1, group2 = data
test_stat = group1.mean() - group2.mean()
return test_stat
DiffMeansOneSided
は、
DiffMeansPermute
から
MakeModel
と
RunModel
を継承します。
唯一の違いは、
TestStatistic
が差の絶対値を取らないことです。この種の検定は、
差の分布の片側しか考えないので、片側検定（
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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.