Write the Matlab code to implement the 3 pmf stemplots

PROBLEM 2. Binomial and Poisson Distributions. As described in class some pmfs (or pdfs) have inherent characleristics that allow them to be described by formulas. To demonstrate this, gencrate THREE side-by-side pmf stem plots for the sae RV (usc the subplot (,3,x) command in MATLAB to gencrate the three subplots). The random variable X is generaled by rolling thrce dice 1,000 times, and then couniing the number of limes you get "hree sixes" i.c. ane 6 on each of the three dice) in 1,000 olls. To make proramming casicr, this is equivalent to the sum of the three dice being equal to "18". The first plot should be the result of stochaslic modeling of rolling three dice; i.e. roll three dicc 1000 times for 10,000 experiments. The second plot is oblained using the binomial distribution: P,(k) p (I-p) 1000 and pis the probability of success in a single roll. When the probability of an oulcome is smail and the numher of esperiments large, the binomial distribution begins to approach the Poisson distribution where the probability of an outcome approaches zero and the number of expements approaches infinity: p-Aewhere A -np F! The third plot will be a plot of the Poisson distribution, and should look similar to the lirst two plots a-e Hm PROBLEM 2. Binomial and Poisson Distributions. As described in class some pmfs (or pdfs) have inherent characleristics that allow them to be described by formulas. To demonstrate this, gencrate THREE side-by-side pmf stem plots for the sae RV (usc the subplot (,3,x) command in MATLAB to gencrate the three subplots). The random variable X is generaled by rolling thrce dice 1,000 times, and then couniing the number of limes you get "hree sixes" i.c. ane 6 on each of the three dice) in 1,000 olls. To make proramming casicr, this is equivalent to the sum of the three dice being equal to "18". The first plot should be the result of stochaslic modeling of rolling three dice; i.e. roll three dicc 1000 times for 10,000 experiments. The second plot is oblained using the binomial distribution: P,(k) p (I-p) 1000 and pis the probability of success in a single roll. When the probability of an oulcome is smail and the numher of esperiments large, the binomial distribution begins to approach the Poisson distribution where the probability of an outcome approaches zero and the number of expements approaches infinity: p-Aewhere A -np F! The third plot will be a plot of the Poisson distribution, and should look similar to the lirst two plots a-e Hm