Q4) By using Matlab: (Archimedes goes to Monte Carlo). A (slow and in fact poor) way...

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Q4) By using Matlab: (Archimedes goes to Monte Carlo). A (slow and in fact poor) way of approximating = 3.141592... is to run a Monte Carlo simulation whereby a uniformly distributed random point is chosen in a square of side 1. If the point falls within a distance of 1 from 0 it is counted a success, otherwise it is a failure. Given that the point is uniformly distributed in the square, the total number of success divided the number of attempts must therefore converge n/4. Write a Monte Carlo method that will compute this. Q4) By using Matlab: (Archimedes goes to Monte Carlo). A (slow and in fact poor) way of approximating = 3.141592... is to run a Monte Carlo simulation whereby a uniformly distributed random point is chosen in a square of side 1. If the point falls within a distance of 1 from 0 it is counted a success, otherwise it is a failure. Given that the point is uniformly distributed in the square, the total number of success divided the number of attempts must therefore converge n/4. Write a Monte Carlo method that will compute this.