#Import required libraries : library(ggplot2)

#Coin flip function : coin_flip <- function(){ return(sample(c(0,1),1)) }

#Check the return value of coin_flip() : coin_flip()

#Monte Carlo Simulation :

#Empty list to store the probability values. list1 <- c()

monte_carlo <- function(n){ results <- 0 for (i in 1:n){ flip_result <- coin_flip() results <- results + flip_result

#Calculating probability value :
prob_value <- results/(i)

#Append the probability values to the list :
list1 <- c(list1,prob_value)

#Plot the results :
plot <- ggplot() +
  geom_hline(yintercept = 0.5, color = 'red', linetype = 'solid') +
  xlab("Iterations") +
  ylab("Probability") +
  geom_line(aes(x=1:length(list1),y=list1)) +
  theme_classic()
print(plot)

} return(results/n) }

#Calling the function : answer <- monte_carlo(5000) print(paste("Final value :",answer))

python代码转R语言代码#Import required libraries import randomimport numpy as npimport matplotlibpyplot as plt#Coin flip function #0 -- Heads#1 -- Tailsdef coin_flip return randomrandint01 #Check the r

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