June 2016
Beginner to intermediate
376 pages
8h 58m
Japanese
Content preview from データ分析によるネットワークセキュリティ
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136
6
章 セキュリティ分析のための
R
入門
One-sample Kolmogorov-Smirnov test
data: a.set
D = 0.0909, p-value = 0.3806
alternative hypothesis: two-sided
> # p
値が大きい……サンプル数が足りないのだろう。
> #
それぞれ
400
のサンプルで再度実行してみる。
> a.set<-runif(400,min=10,max=20)
> b.set<-runif(400,min=10,max=20)
> #
相互を比較する。
> ks.test(a.set,b.set)$p.value
[1] 0.6993742
> #
分布と比較する。
> ks.test(a.set,punif,min=min(a.set),max=max(a.set))$p.value
[1] 0.5499412
> #
別の分布と比較する。
> ks.test(a.set,pnorm, mean = mean(a.set),sd=sd(a.set))$p.value
[1] 0.001640407
KS検定は検出力が弱い検定である。検出力とは、帰無仮説を正しく棄却できる能力を表す。検出
力の弱い検定は、検出力の強い検定よりも多くのサンプルを必要とする。特にセキュリティデータを
扱う場合には、サンプルサイズは複雑な問題である。統計的検定のほとんどはウェットラボ（生物実
験を行う研究室）の世界から来ており、この世界では60のサンプルを得ればちょ ...
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