Please include explanations for code.

2. (30 points) (With Python) In this Python exercise, you will compute the probability that your professor goes to ruin and loses all her money. Be sure to annotate your code with short explanations of what you are doing (worth 10 points) Suppose (as above) that your professor starts with $15 and begins playing the betting game. (a) Simulate the gambler's ruin problem for your professor who starts with $15 and quits when she reaches $45 or goes bust. Use your code to simulate the probability of eventual ruin. Be sure to print your results. For example, print ('The probability that my professor eventually loses all of her money is %. 3f., %prob0fRuin) Start by simulating 500 sample paths of the Markov chain (Xn)n=0. Find the probability that your professor loses all of her money (b) Using the simulated sample paths in part (a), compute the probability that your professor reaches $45. Print your results as in part (a) (c) Take a screenshot showing your code and your results together (e.g. side by side) 2. (30 points) (With Python) In this Python exercise, you will compute the probability that your professor goes to ruin and loses all her money. Be sure to annotate your code with short explanations of what you are doing (worth 10 points) Suppose (as above) that your professor starts with $15 and begins playing the betting game. (a) Simulate the gambler's ruin problem for your professor who starts with $15 and quits when she reaches $45 or goes bust. Use your code to simulate the probability of eventual ruin. Be sure to print your results. For example, print ('The probability that my professor eventually loses all of her money is %. 3f., %prob0fRuin) Start by simulating 500 sample paths of the Markov chain (Xn)n=0. Find the probability that your professor loses all of her money (b) Using the simulated sample paths in part (a), compute the probability that your professor reaches $45. Print your results as in part (a) (c) Take a screenshot showing your code and your results together (e.g. side by side)