The company cannot predict whether the pandemic death rate will stay stable. Set the seed to 29, then write a Monte Carlo simulation that for each of B = 10000 iterations: - randomly changesp by adding a value between -0.01 and 0.01 with sample(seq(0. 01, 0. 01, length = 100), 1) - uses the new random p to generate a sample of n = 11000 policies with premium 1: and loss per claim I = 150000 - returns the profit over 11 policies {sum of random variable) (IMPORTANT! If you use R 3.6 or laterr you will need to use the command set. seed (3;, sample. kind = \"Rounding\") instead of set. seed(x) . Your R version will be printed at the top of the Console window when you start RStudio.) The outcome should be a vector of B total profits. Use the results of the Monte Carlo simulation to answer the following three questions. (Hint: Use the process from lecture for modeling a situation for loans that changes the probability of default for all borrowers simultaneously.) Question 6a 0.0!10 point {graded} What is the expected value over 1,000 policies