v1 = seq(-3,3,0.1)
v2 = v1^2
plot(x = v1, y = v2)
plot(v1, v2, col = 'red')
plot(v1, v2, col=“red”, pch = 20)
plot(v1, v2, col="red", pch = 20, cex = 3)
plot(v1, v2, type = "l")
plot(v1, v2,type="l",lty=4,lwd=3)

plot(v1, v2, main = "THIS IS THE TITLE", 
     xlab = "Label for X-axis",
     ylab = "Label for Y-axis")

plot(v1, v2, main = "THIS IS THE TITLE", cex.lab = 1.5,
     xlab = "Label for X-axis",ylab = "Label for Y-axis")


plot(v1, v2, main = "TITLE", xlab = "X here",ylab = "Y here",
     xlim = c(-3.5, 3.5), 
     ylim = c(-0.5, 10))

plot(v1, v2, col = "blue", type = "o", lty = 2, pch = 19, 
     cex.lab = 1.5, lwd = 3, main = "Y=X*X", xlab = "X", 
     ylab="X*X", xlim=c(-3.5,3.5), ylim=c(-0.5, 10))

dat<- read.csv("http://www.matsuka.info/data_folder/datWA01.txt")
hist(dat$h)
hist(dat$h, breaks = 20, main = "Histogram of Height", 
     xlab = "Height", col = 'blue', xlim = c(140, 190))

dens<-density(dat$h); # 確率密度の算出
hist(dat$h, main = "Histogram of Height", xlab = "Height",  
     xlim = c(140,190), probability = T)
lines(dens, lwd = 2, col = "red", lty=2) 

plot(v1, v2, col = "blue", type = "l", pch = 19, cex.lab = 1.5, lwd = 3, xlab = "X", 
     ylab="f(X)", xlim=c(-3.5,3.5), ylim=c(-0.5, 10))
lines(v1, v1^3, col='red',lwd = 3)
legend("bottomright", c("x^2","x^3"), col=c('blue','red'), lwd=2)


boxplot(dat$h,main="Boxplot of Height", ylab="Height", col='cyan', ylim=c(140,190))
boxplot(dat$h,main="Boxplot of Height", xlab="Height", col='orange', horizontal=T)


boxplot(dat$h ~ dat$gender,
        main="Distribution of Height by Gender", 
        ylab="Gender", xlab="Height", col=c('blue','cyan'),
        ylim=c(140,190), horizontal=T)

dat<-read.table("http://www.matsuka.info/data_folder/aov01.txt")
boxplot(dat$h ~ dat$gender + dat$affil, 
        main="Distribution of  Height by Gender and Affiliation",   
        ylab="Gender x Affiliation", xlab="Height", col=c("blue","cyan","red","magenta"), 
        ylim=c(140,190),horizontal=T)

interaction.plot(dat$gender,
                 dat$affil,
                 dat$h, 
                 pch=c(20,20), 
                 col=c("skyblue","orange"), 
                 xlab="gender", ylab="height", 
                 lwd=3,type='b',cex=2,
                 trace.label="Affiliation")

par(mfrow=c(1,2)) 
hist(dat[dat$gender=="F",]$h, main="Dist. of Height for Female Participants", xlab="Height", xlim=c(140,190), probability=T)
dens.F = density(dat[dat$gender=='F',]$h)
lines(dens.F, col='blue',lwd=2) 
hist(dat[dat$gender=="M",]$h, main="Dist. of Height for Male 
     Participants", xlab="Height", xlim=c(140,190), probability=T,ylim=c(0,0.08))
dens.M = density(dat[dat$gender=='M',]$h)
lines(dens.M, col='green', lwd=2)

par(mfrow=c(1,1))
plot(dens.F,col='blue',lwd=2, ylab='density', xlim=c(140,190), main="Dist. of Height by gender",xlab='Height')  
lines(dens.M,col='green',lwd=2)
legend("topleft", c('Female','Male'), col=c('blue','green'), cex=1.2,lwd=2)

plot(dat$shoesize, dat$h, main="Relationship b/w shoesize and height",
   xlab = "shoesize", ylab="height", pch=19, col="red")