20190123生物科学基礎実験II 生物統計学
提供: 広島大学デジタル博物館
生物科学基礎実験II 生物統計学(2019年1月23日)
Rのダウンロード
Rを使った統計処理で参考になるサイト
- Rによる統計処理(群馬大学青木先生)http://aoki2.si.gunma-u.ac.jp/R/
ソース
x <- c(7.4,7.2,6.5,7.0,7.6,6.8,7.8,7.3,7.7,7.5,7.1,7.7,7.1,6.8,7.3,6.9,6.7,7.1,7.2,7.6,7.6,7.5,7.8,7.5,7.2,7.4,7.0,7.1,7.3,7.6) x sum(x) y <- c(0.056,0.059,0.046,0.052,0.059,0.056,0.063,0.058,0.063,0.047,0.044,0.048,0.050,0.045,0.061,0.053,0.046,0.050,0.055,0.055,0.058,0.052,0.059,0.056,0.043,0.047,0.046,0.057,0.054,0.063) y var(y) sum(y) sum(x) mean(x) median(x) which.max(table(x)) var(x) sd(x) max(x) min(x) range(x) var(x) var(y) var(x,y) cor(x,y) waido <- function(x) mean((x-mean(x))^3)/(sd(x)^3) waido(x) waido(y) sendo <- function(x) mean((x-mean(x))^4)/(sd(x)^4) sendo(x) sendo(y) hist(x) boxplot(x,names=c("x")) boxplot(x,y)
y ymg <- y*1000 ymg
species length A 3.3 A 6.5 A 2.6 B 9.0 B 8.1 B 7.7
z <- read.delim("clipboard") z z[1] z[2] z$species z$length sum(z$length)
read.csv("data20190123a.csv") q <- read.csv("data20190123a.csv") q
data(iris) iris mean(iris$Sepal.Length)
source("http://aoki2.si.gunma-u.ac.jp/R/src/all.R", encoding="euc-jp") result1 <- pca(iris[1:4]) result1 result1$mean result1$variance result1$r result1$fs result1$eval result1$factor.loadings plot(result1$fs[,1:2],pch=as.integer(iris$Species)) plot(result1$fs[,1], result1$fs[,3],pch=as.integer(iris$Species)) plot(result1$fs[,2], result1$fs[,3],pch=as.integer(iris$Species))
data(iris) source("http://aoki2.si.gunma-u.ac.jp/R/src/all.R", encoding="euc-jp") result2 <- candis(iris[1:4],iris[5]) result2 plot(result2$can.score,type="n") points(result2$can.score,pch=as.integer(iris$Species))