## Exercise 1
a <- sample(100,20)
max(a); min(a); median(a); sum(a)


## Exercise 2
N <- 10
factorial(N)
prod(1:N)

N <- 10
sum(1/1:N)

## Exercise 3
a <- sample(-20:20,10)
a <- sample(seq(-20,20,length.out=1000),10)

sum(a[a>=0])
sum(a[a<0])
max(sum(a[a>=0]),abs(sum(a[a<0])))

## Exercise 4
N <- 10
sum(1/1:N)

## Exercise 5
a <- rnorm(1000,2,0.6)
mean(a); sd(a); quantile(a)


## Exercise 6
A <- matrix(c(1:3,4,2,1,2,3,0),ncol=3, byrow=TRUE)
t(A); solve(A); A %*% solve(A)


## Exercise 7
Age <- c(33, 33, 42, 33, 26, 37, 323, 45, 31, 49)
Temp <- c(97.00, 98.80, 96.20, 97.80, 98.80, 101.30, 97.80, 97.40, 99.20, 99.20)
df <- data.frame(Age, Temp)
df$TempC <- (df$Temp - 32)*(5/9)
df$Gender <- factor(c("M", "M", "M", "F", "F", "M", "F", "F", "F", "M"))
mean(df$TempC[df$Gender=="M"])
mean(df$TempC[df$Gender=="F"])


## Exercise 8
mydf <- read.table("example1/BodyTemperature.txt", header=TRUE, sep=" ")
nrow(mydf); ncol(mydf); dim(mydf)

class(mydf)
mode(mydf)
mydf$TemperatureC <- (mydf$Temperature - 32)*(5/9)
mean(mydf$HeartRate)
mean(mydf$HeartRate[mydf$Gender=="M"])
mean(mydf$HeartRate[mydf$Gender=="F"])
mean(mydf$HeartRate[mydf$Age>40])
max(mydf$TemperatureC[mydf$Age<40])