Modify Bernoulli (Program 2.2.6) to animate the bar graph, replotting it after each experiment, so that you can watch it converge to the Gaussian distribution. Then add a command-line argument and an overloaded binomia () implementation to allow you to specify the probability \(p\) that a biased coin comes up heads, and run experiments to get a feeling for the distribution corresponding to a biased coin. Be sure to try values of \(p\) that are close to 0 and close to 1 .

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Program 2.2.6 Bernoulli trials public class Bernoulli { public static int binomial (int n) { // Simulate flipping a coin n times; return # heads. } int heads 0; for (int i = 0; i < n; i++) if (StdRandom.bernoulli (0.5)) heads++; return heads; public static void main(String[] args) { // Perform Bernoulli trials, plot results and model. int n = Integer.parseInt(args[0]); int trials = Integer.parseInt(args[1]); n number of flips per trial int[] freq = new int[n+1]; trials number of trials for (int t = 0; t < trials; t++) freq [binomial (n)]++; freq[] experimental results double[] norm = new double[n+1]; norm[] normalized results for (int i = 0; i