Problem 3: In lab lecture notes and demo code, t is shown how to simulate random samples from Exp() to verify classical central limit theorem numerically. It is also stressed that no matter what type of random samples you use, the standardized partial sum Sn always converge to N(0,1). In this problem, simulate random samples from the following distributions 1. Bernoulli(0.5) (so that 0.5 and 2-0.25). (Hint: You can use rbinom to generate Bernoulli random numbers.) 2. Uniform (0, l) (so that -0.5 and 2-1/12). 3. Possion(1) (so that -1 and 2-1). For each case, set the number of simulations N to be 1000 and for each simulation, generate n 2000 random numbers. Report 3 pieces of code, 3 Q-Q plots and your conclusion. You only need to slightly modify the demo code to get the right