We evaluated three card probabilities in the previous post. It is important to verify the calculations, well, by actually counting the occurrences by shuffling it a million times and drawing five cards. But first, build the deck:
suits <- c("Diamonds", "Spades", "Hearts", "Clubs")
face <- c("Jack", "Queen", "King")
numb <- c("Deuce", "Three", "Four", "Five", "Six", "Seven", "Eight", "Nine", "Ten")
face_card <- expand.grid(Face = face, Suit = suits)
face_card <- paste(face_card$Face, face_card$Suit)
numb_card <- expand.grid(Numb = numb, Suit = suits)
numb_card <- paste(numb_card$Numb, numb_card$Suit)
Aces <- paste("Ace", suits)
deck <- c(Aces, numb_card, face_card)Four face cards
itr <- 1000000
shuff <- replicate(itr, {
draw <- sample(deck, 5, replace = FALSE, prob = rep(1/52, 52))
dr <- sum(str_detect(draw, "Queen|King|Jack"))
if(dr == 4){
counter <- 1
}else{ counter <- 0}
})
mean(shuff)The answer turns out to be: 0.007548
Three cards are kings
itr <- 1000000
shuff <- replicate(itr, {
draw <- sample(deck, 5, replace = FALSE, prob = rep(1/52, 52))
dr <- sum(str_detect(draw, "King"))
if(dr == 3 ){
counter <- 1
}else{ counter <- 0}
})
mean(shuff)0.001717All five cards are hearts
itr <- 1000000
shuff <- replicate(itr, {
draw <- sample(deck, 5, replace = FALSE, prob = rep(1/52, 52))
dr <- sum(str_detect(draw, "Hearts"))
if(dr == 5 ){
counter <- 1
}else{ counter <- 0}
})
mean(shuff)0.00048
