4.35 Roulette winnings.

Let’s see what this looks like as plotted

barplot(roulette$odds, main = "Binomoal Distribution for Betting on Red for Three Roulette Spins",
        names.arg=c(winnings))

roulette[,3:4] <- sapply(roulette[,3:4], as.numeric)
win <-  roulette %>% filter(value >0) %>% summarise(odds = sum(odds))
lose <-  roulette %>% filter(value < 0) %>% summarise(odds = sum(odds))
odds <- rbind(win,lose)
outcome <-rbind("win", "lose")
win_lose <- cbind(outcome, odds)

kable(win_lose, "html") %>% kable_styling("striped") %>% scroll_box(width = "100%", height = "100%")
outcome odds
win 0.4610352
lose 0.5389648
roulette[2] <- sapply(roulette[2], as.numeric)
win_lose <- win_lose %>% mutate(total = (odds * 100))

bp<- ggplot((win_lose), aes(x=NA, y=total, fill=outcome))+
geom_bar(width = 1, stat = "identity")
pie <- bp + coord_polar("y", start=0)
pie + scale_fill_grey() + theme_minimal()