myscratchpad

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# 足立浩平 (2006). 多変量データ解析法――心理・教育・社会系のための入門――　ナカニシヤ出版


# 表2.1　p16
mat <- matrix(c(3.2,3.4,3,3.2,4.2,4,4,3.7,3.6,3.6,3.7,3.4,3.2,3.2,2.7,3.5,3.2,3.2,4.6,4,4.8,4.6,4.3,3.6,3.2,3.7,3.2,3.8,3.7,3.4,3.5,3.5,4.5,3.8,3.9,4.1,3.7,3.5,3.7,3.5,3.6,3.8,2.8,2.5,2.2,2.6,3.1,3.4,3.5,3.4,2.9,3.5,3.9,3.1,2.9,2.8,2.6,2.2,2.1,2.5,3,3.2,3.8,4,3.5,4.2,4.7,2.7,2.2,2.3,2.6,2.6,2.2,2.6,3.2,3.1,3.7,4.1,3.6,4.2,4.7,2.4,2.5,2.4,2.2,3.2,3.3,3.6,2.8,2.4,3.2,4.3,4.7,3.5,4.9,2.3,3.3,3.9,1.4,2.1,3.4,2.9,3.3,1.5,2.1,3.4,4.2,3.5,3.5,1.8,3.3,2.5,1.7,3.6,4.1,4.2,4.1,1.6,2.6,3.5,4.1,3.7,4.2,2.3,3.4,4.7,3.3,4.1,3.4,3.2,4.5,3.7,3.7,4.2,3.9,3.5,3.7,3.3,2.8,3.9,3.8,4.7,1.3,1.5,2.3,3.9,3.6,4.4,3.7,2.5,2.8,2.9,1.8,2.3,1.8,4.2,4.3,4,4.9,3,4.5,4,5,3.5,4.1,3.3,4.3,4.3),
nr=14,
dimnames=list(c("僧侶", "銀行員", "漫画家", "デザイナー", "保母", "大学教授", "医師", "警察官", "新聞記者", "船乗り", "プロスポーツ選手", "作家", "俳優", "スチュワーデス"),
c("立派な", "役立つ", "よい", "大きい", "力がある", "強い", "速い", "騒がしい", "若い", "誠実な", "かたい", "忙しい"))
)

# 表　3.1　p22
ppt <- c(88,52,77,35,60,97,48,66,78)
wrt <- c(70,78,87,40,43,95,62,66,50)
int <- c(65,88,89,43,40,91,83,65,48)
dat <- data.frame(ppt, wrt, int)
mean(dat)

# 表　3.2　p28
ppt <- c(77,60,97,35,66,48,78,52,88)
wrt <- c(18,8,20,8,14,12,10,16,14)
int <- c(45,20,45,22,32,41,24,44,32)
dat <- data.frame(ppt, wrt, int)
mean(dat)

# 表8-1　p76
se <- c(9,2,5,4,6,4,6,6,7,4,5,6,7,4,3,5,4,7,5,5,6,4,3,7,4,5,3,4,6,5,4,3,5,5,2,4,7,5,6,5,3,5,6,5,5,2,5,5,7,6,6,6,7,7,4,7,7,6,6,4,4,6,4,2,5,4,4,5,6,4,6,6,6,5,6,4,7,8,8,4,4,5,6,8,4,5,4,3,4,5,3,3,6,4,5,4,3,4,5,4)
yo <- c(7,3,6,6,5,5,7,6,6,4,6,4,5,5,6,6,5,6,7,5,7,6,6,7,6,6,5,6,5,6,3,3,5,6,5,6,7,7,5,5,4,7,4,7,7,5,9,5,6,5,6,6,6,6,4,6,5,6,5,4,6,4,5,6,6,5,6,4,6,6,5,7,5,6,6,4,5,6,5,5,6,6,6,6,6,7,4,5,6,6,5,3,6,5,7,4,7,7,4,5)
sa <- c(9,5,7,6,7,5,6,7,8,6,6,6,8,6,5,7,8,8,7,7,7,6,5,8,7,5,4,6,9,8,7,6,6,7,5,7,9,5,7,4,6,7,7,5,9,4,6,7,8,6,7,8,8,7,6,8,8,6,7,7,6,5,6,5,6,4,6,7,7,5,7,8,8,6,8,5,7,9,8,3,5,7,7,6,6,7,5,6,6,7,6,6,8,5,6,6,6,5,5,7)
bu <- c(2,8,6,3,6,5,5,4,5,8,4,5,5,7,6,3,4,4,4,5,4,4,7,5,6,4,6,5,5,5,7,9,7,5,5,7,5,3,4,7,9,6,7,4,3,7,4,8,5,7,3,4,4,5,8,3,6,3,6,6,5,7,6,5,6,7,4,6,4,7,5,5,5,6,5,6,6,6,4,6,6,6,6,7,6,4,9,6,5,6,7,7,5,6,4,7,4,6,9,7)
ha <- c(9,1,8,8,6,6,8,8,6,4,6,5,5,5,4,9,8,6,9,4,8,5,4,7,5,8,5,5,8,6,4,3,5,4,5,5,6,8,7,5,4,6,5,9,8,3,9,4,7,4,6,8,8,7,2,7,7,6,5,4,6,4,6,5,7,5,7,6,7,5,5,7,6,6,6,5,5,6,6,5,5,5,4,6,6,8,2,4,6,5,5,3,5,6,6,3,7,7,4,3)
ya <- c(8,3,4,5,5,3,3,7,5,3,4,6,6,4,2,5,5,6,5,4,6,3,3,8,4,5,4,4,6,6,5,4,6,4,3,5,8,5,6,3,3,4,5,6,7,4,4,5,7,6,5,8,6,6,3,8,6,4,5,5,5,3,4,2,6,3,4,8,4,4,6,7,6,2,6,4,7,8,9,3,4,4,4,8,5,6,2,3,4,4,4,3,7,4,6,5,3,3,5,5)
ch <- c(3,7,6,7,6,5,6,6,3,6,5,4,7,7,6,7,5,4,4,6,6,7,8,5,5,4,6,7,5,6,5,7,6,8,6,6,3,5,2,8,6,6,5,5,3,6,4,3,2,5,6,3,4,5,7,2,2,3,3,5,9,5,7,9,5,7,6,4,5,6,4,4,2,8,3,5,3,1,2,6,6,6,3,2,6,5,8,7,9,6,9,7,3,8,3,6,7,7,6,4)
ni <- c(8,3,6,7,6,5,8,7,4,3,7,6,6,5,5,7,6,6,7,8,6,5,2,6,6,7,5,5,6,6,5,3,5,8,5,5,5,5,7,4,4,7,4,6,7,5,8,5,6,4,7,9,7,7,3,7,6,4,7,4,6,4,5,5,6,5,6,4,8,6,6,7,5,5,6,3,6,7,7,5,5,5,5,7,6,9,4,4,6,6,5,4,7,5,5,5,5,4,7,3)
dat <- data.frame(se, yo, sa, bu, ha, ya, ch, ni)


# 表15.1　p150
grp <- rep(c("a", "b"), c(15, 12))
sha  <- c(15,11,16,19,18,15,17,12,13,14,16,11,20,15,13,11,10,11,10,10,13,11,15,12,10,12,10)
kyo  <- c(14,13,14,21,26,28,19,15,22,26,20,15,21,20,13,15,13,14,10,14,19,10,20,22,11,10,14)
kin  <- c(15,17,17,18,21,18,12,18,16,18,18,20,17,19,17,18,16,24,13,22,23,20,20,23,18,19,21)
shi  <- c(14,17,26,15,15,12,10,12,10,6,18,15,20,12,16,17,9,16,12,18,24,28,16,13,10,27,19) 
dat <- data.frame(grp, sha, kyo, kin, shi)


# 表15.4　p153
grp   <- factor(c(1,1,1,1,2,2,2,3,3,3,3,4,4,4,4,4,5,5,5,5))
sak  <- c(9,6,6,4,7,1,4,5,5,3,6,8,4,10,5,5,4,5,1,6)
ens   <- c(8,8,6,8,10,9,9,4,5,5,5,6,6,5,6,3,6,4,4,4)
tmp   <- c(2,5,4,8,5,9,7,9,10,8,7,4,7,6,6,8,3,2,1,4)
mss  <- c(6,7,8,8,6,7,5,6,7,5,5,4,4,3,3,5,5,6,5,4) 
arg   <- c(10,6,5,7,4,7,6,0,7,3,5,5,1,10,2,3,7,5,3,6)
org   <- c(7,9,5,6,3,4,6,8,5,5,6,6,5,6,4,5,6,9,7,10)
dat <- data.frame(grp, sak, ens, tmp, mss, arg, org)