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--- normal_distribution [2017/03/24 08:39] – hkimscil
+++ normal_distribution [2024/03/13 08:28] (current) – hkimscil
@@ Line 5: / Line 5: @@
 \displaystyle P(x) = \frac{1}{\sqrt{2 \pi \sigma^2}} * e^{\frac{-(x - \mu)^2}{2 \sigma^2}}
 \end{equation}
 위에서 $\pi$와  $e$ 는 각각 $\pi = 3.1416, e=2.7183 $으로 상수
+특히 평균이 0 이고 그 표준편차가 1인 정상분포를 표준정상분포라고 한다.
+{{http://math.arizona.edu/~rsims/ma464/standardnormaltable.pdf|표준정규분포 table}}
+https://www.mathsisfun.com/data/standard-normal-distribution-table.html
+<code>set.seed(3000)
+xseq<-seq(-4,4,.01)
+densities<-dnorm(xseq, 0,1)
+cumulative<-pnorm(xseq, 0, 1)
+randomdeviates<-rnorm(1000,0,1)
+par(mfrow=c(2,2), mar=c(3,4,4,2))
+plot(xseq, densities, col="darkgreen",
+   xlab="", ylab="Density", type="l", lwd=2, cex=2,
+   main="PDF of Standard Normal", cex.axis=.8)
+plot(xseq, cumulative, col="darkorange",
+   xlab="", ylab="Cumulative Probability",type="l",lwd=2, cex=2,
+   main="CDF of Standard Normal", cex.axis=.8)
+hist(randomdeviates, main="Random draws from Std Normal",
+   cex.axis=.8, xlim=c(-4,4))
+xseq<-seq(-4,4,.01)
+y<-2*xseq + rnorm(length(xseq),0,5.5)
+hist(y, prob=TRUE, ylim=c(0,.06), breaks=20)
+curve(dnorm(x, mean(y), sd(y)), add=TRUE, col="darkblue", lwd=2)
+par(mfrow=c(1,1))
+</code>
+{{:pasted:20240313-082705.png}}