EXERCISE 1:
c <- read.table("http://www.stat.ucla.edu/~nchristo/statistics13/countries_life.txt", header=TRUE)

#Part (a):
plot(c$Income, c$Life)
#Comment:  As the Income increases we see see an increase of Life.  But #when Income > $1000 the life expectancy levels off.

#Part (b):
boxplot(c$Income)
boxplot(c$Life)

hist(c$Income)
hist(c$Life)

#Or you can use the UsingR package:
library(UsingR)
simple.hist.and.boxplot(c$Income)
simple.hist.and.boxplot(c$Life)


#Part (c):
c1 <- c[which(c$Income<1000), ]
c2 <- c[which(c$Income>1000), ]


#Part (d):
plot(c1$Income, c1$Life)
cor(c1$Income, c1$Life)

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EXERCISE 2:
d <- read.table("http://www.stat.ucla.edu/~nchristo/statistics13/body_fat.txt", header=TRUE)


#Part (a):
summary(d$y)

var(d$y)

sd(d$y)


#Part (b):
boxplot(d$y)
hist(d$y)

#Or you can use the UsingR package:
library(UsingR)
simple.hist.and.boxplot(d$y)


#Part(c):
d1 <- d[which(d$x3<30), ]
d2 <- d[which(d$x3>60), ]

boxplot(d1$y, d2$y)


#Part (d):
summary(d1$y)
var(d1$y)
sd(d1$y)

summary(d2$y)
var(d2$y)
sd(d2$y)


#Part (e):
cor(d1$y, d1$x10)
cor(d2$y, d2$x10)


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EXERCISE 3:
a <- read.table("http://www.stat.ucla.edu/~nchristo/statistics13/soil.txt", header=TRUE)

#Part (a):
summary(a$lead)
summary(a$zinc)

var(a$lead)
var(a$zinc)

sd(a$lead)
sd(a$zinc)


#Part (b):
hist(a$lead)

loglead <- log(a$lead)
hist(loglead)


#Part (c):
logzinc <- log(a$zinc)
plot(logzinc, loglead)

#Part (d):
lead_colors <- c("green", "yellow", "orange") 
lead_levels <- cut(a$lead, c(0, 150, 400, max(a$lead))) 
 
plot(a$x, a$y, "n", xlab="x", ylab="y") 

points(a$x, a$y, cex=a$lead/mean(a$lead), col=lead_colors[as.numeric(lead_levels)], pch=19) 


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EXERCISE 4:
b <- read.table("http://www.stat.ucla.edu/~nchristo/statistics13/la_data.txt", header=TRUE) 

#Part (a):
library(maps) 
range(b$Longitude) 
#[1] -118.6322 -118.1746 
range(b$Latitude) 
#[1] 33.780 34.313 

#Comment:  I computed the range for Longitude and Latitude so that we can #have an idea about where to extend the map.  See the command below.

plot(b$Longitude, b$Latitude, xlab="Longitude", ylab="Latitude", 
xlim=c(-118.8, -118.1), ylim=c(33.7, 34.4)) 

map("county", "ca", add=TRUE) 

#Part (b):
plot(b$Income, b$Schools)


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