If

x <- 5
if(x > 0){
print("Positive number")
}

## [1] "Positive number"

x <- -5
if(x > 0){
print("Non-negative number")
} else {
print("Negative number")
}

## [1] "Negative number"

x <- 0
if (x < 0) {
print("Negative number")
} else if (x > 0) {
print("Positive number")
} else
print("Zero")

## [1] "Zero"

# Create vector quantiy
x <-  10
# Create multiple condition statement
if (x <20) {
      print('Good')
} else if (x > 20  &x <= 30) {
     print('Average')
} else {
      print('Bad!')
}

## [1] "Good"

Product <- 'A'
price <- 100
if (Product =='A'){
  cat('3% discount is applied.','The discounted price is',price-price *0.03)  
} else if (Product =='B'){
    cat('15% discount is applied.','The discounted price is',price-price *0.15)  
} else {
    cat('30% discount is applied.','The discounted price is',price-price *0.3)  
}

## 3% discount is applied. The discounted price is 97

For

for(i in 1:5)
  print(i^2)

## [1] 1
## [1] 4
## [1] 9
## [1] 16
## [1] 25

for(i in 1:5) 
  print(1:i)

## [1] 1
## [1] 1 2
## [1] 1 2 3
## [1] 1 2 3 4
## [1] 1 2 3 4 5

n <- 6 # sample size
n_iter <- 10^5 # number of iterations of loop (equivalent to p)
means <- numeric(n_iter)
sds <- numeric(n_iter)
sems <- numeric(n_iter)
for(i in 1:n_iter){
  y <- rnorm(n) # mean=0 and sd=1 are default so not necessary to specify
  means[i] <- mean(y)
  sds[i] <- sd(y)
  sems[i] <- sd(y)/sqrt(n)
}
sd(means)

## [1] 0.4069374

mean(sems)

## [1] 0.3885883

While

i <- 1
N <- c(1:20)
numsum = 0
while (numsum<100) {
  numsum = numsum + N[i]
  i = i + 1
  print(numsum)
}

## [1] 1
## [1] 3
## [1] 6
## [1] 10
## [1] 15
## [1] 21
## [1] 28
## [1] 36
## [1] 45
## [1] 55
## [1] 66
## [1] 78
## [1] 91
## [1] 105