#
#	20100827.R
#

#	Bivariate analysis

# Read in the data
data <- read.csv("data1-3a.csv")
attach(data)

# See the data
data

# A feel for the data (univariate)
mean(x)
median(x)
sd(x)
IQR(x)
boxplot(x)

mean(y)
median(y)
sd(y)
IQR(y)
boxplot(y)

# Of x and y together, individually
boxplot(x,y, notch=TRUE, names=c("x","y"))


# Of x and y together, showing a relationship: a scatterplot
plot(x,y)

# A better scatterplot:
plot(x,y, xlim=c(0,600), ylim=c(-1000, 2000), xlab="x-value", ylab="y-value",
	main="Scatterplot of y against x", pch=16, col="blue", lwd=2, las=1)


# What is that line of best fit?
model1 <- lm(y~x)
abline(model1$coef[[1]],model1$coef[[2]], col="red", lwd=2)


#
#	This linear model (lm) will be explained in the future. No worries.