# -- ���K1 -----------------------------
(3^2-5)/4

a <- 2
b <- 3
c <- 1
(-b+(b^2-4*a*c)^(-2))/(2*a)

d <- c(4, 9, 25, 36)
sqrt(d)


# -- ���K2 -----------------------------
dat <- read.csv("grade1.csv")
apply(dat[,2:5], 2, sd)
plot(dat[,3], dat[,4])
plot(dat$Participation, dat$Written)


# -- ���K3 -----------------------------
mcn <- read.csv("machine5.csv")
tapply(mcn$Weight, list(mcn$MachineID, mcn$Period), mean)
tapply(mcn$Weight, list(mcn$MachineID, mcn$Period), var)
tapply(mcn$Weight, list(mcn$MachineID, mcn$Period), sd)

boxplot(mcn$Weight~mcn$MachineID)
stripchart(mcn$Weight~mcn$MachineID, vertical = TRUE, pch = 21, col = "maroon", bg ="orange",method = "jitter", add = TRUE)
boxplot(mcn$Weight~mcn$Period)
stripchart(mcn$Weight~mcn$Period, vertical = TRUE, pch = 21, col = "maroon", bg ="orange",method = "jitter", add = TRUE)

case <- paste(mcn$MachineID, mcn$Period)
boxplot(mcn$Weight~case)
stripchart(mcn$Weight~case, vertical = TRUE, pch = 21, col = "maroon", bg ="orange",method = "jitter", add = TRUE)


# -- ���K4 -----------------------------
cst <- read.csv("customer.csv")
table(cst$Branch, cst$Sex)

str <- read.csv("store.csv", row.names="branch")
lm.str <- lm(sales~., data=str)
summary(lm.str)
x1 <- c(1, 1956,  3, 88, 42, 10, 120)
x2 <- c(1, 1300, 12, 90, 45, 10, 100)
x3 <- c(1, 1423,  8, 42, 36, 10,  90)
t(lm.str$coef) %*% x1
t(lm.str$coef) %*% x2
t(lm.str$coef) %*% x3


# -- ���K5 -----------------------------
epw <- read.csv("EPower1.csv")
cor(epw$Temp, epw$Power.Max)
lm.epw <- lm(epw$Power.Max~epw$Temp)
summary(lm.epw)

epw[45:47,3] <- epw[1,3]
ep.n <- epw[epw$Day==" N",]
ep.h <- epw[epw$Day==" H",]
lm.ep.n <- lm(ep.n$Power.Max~ep.n$Temp)
summary(lm.ep.n)
lm.ep.h <- lm(ep.h$Power.Max~ep.h$Temp)
summary(lm.ep.h)