# A/B test in R using a Z-test for proportions with 'prop.test' from base R
library(stats)

ab_test <- function(n_A, conv_A, n_B, conv_B, alpha=0.05) {
  # Data
  successes <- c(conv_A, conv_B)
  trials <- c(n_A, n_B)
  
  # Perform proportion test
  test_result <- prop.test(successes, trials, alternative = "two.sided", conf.level = 1 - alpha)
  
  # Results
  cat(sprintf("Conversion rate A: %.4f\n", successes[1] / trials[1]))
  cat(sprintf("Conversion rate B: %.4f\n", successes[2] / trials[2]))
  cat(sprintf("Z-score: %.4f\n", sqrt(test_result$statistic)))
  cat(sprintf("p-value: %.4f\n", test_result$p.value))
  cat(sprintf("95%% confidence interval: (%.4f, %.4f)\n", test_result$conf.int[1], test_result$conf.int[2]))
  
  # Conclusion
  if (test_result$p.value < alpha) {
    cat("Statistically significant difference! Implement version B.\n")
  } else {
    cat("No statistically significant difference.\n")
  }
}

# Example data: Group A (5000 visitors, 250 conversions) and Group B (5000 visitors, 300 conversions)
ab_test(n_A=5000, conv_A=250, n_B=5000, conv_B=300)