### ex2.1 ###### 

?attitude
summary(attitude)
dim(attitude)
nrow(attitude)
ncol(attitude)

result <- lm(rating ~ complaints, data = attitude)
summary(result)

rating <- attitude$rating
mean(rating)
sd(rating)

apply(attitude, 2, mean)
apply(attitude, 2, sd)
colMeans(attitude)

### ex2.2 ######

a <- 5
b <- 1 - ((a^2)/5)

(a >= 2) & (a <= 4)

select1 <- attitude$rating > 50
attitude[select1, ]

cond1 <- attitude$rating > mean(attitude$rating)
cond2 <- attitude$complaints > mean(attitude$complaints)
select2 <- cond1 & cond2
attitude[select2, ]

select3 <- ((1:nrow(attitude))%%3) == 0
attitude[select3, ]

newvar <- attitude$rating > 50
attitude2 <- data.frame(attitude, highrate = newvar)

vec1 <- c(3, 6, 8, 9)
vec2 <- 1:4
vec1 + vec2

scale(attitude$rating)
scale(attitude)

##### Assignment 2

f2 <- faithful

ord <- order(f2$eruptions)
f3 <- f2[ord, ]

f3[5, 2] <- f3[3, 1] <- f3[15, 1] <- NA
summary(f3)

f100 <- f3[1:100, ]

apply(f3, 2, mean, na.rm = TRUE)
apply(f3, 2, sd, na.rm = TRUE)
apply(f100, 2, mean, na.rm = TRUE)
apply(f100, 2, sd, na.rm = TRUE)

FUN <- function(x) {
	return(c(mean(x, na.rm = TRUE), sd(x, na.rm = TRUE)))
}

apply(f3, 2, FUN)
apply(f100, 2, FUN)

obj <- lm(waiting ~ eruptions, data = faithful)
summary(obj)