Week 0 - Activity 3

MONTE CARLO SIMULATIONS:

Monte Carlo Simulations are broad class of computational algorithms that rely on repeated random sampling to obtain numerical results . The underlying concept is to use randomness to solve problems that might be deterministic in principle . They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to use other approaches . Monte Carlo methods are mainly used in three problem classes : Optimizations , Numerical integrations and generating draws from a probability distribution . 

Here I have considered an experiment of tossing a coin . Let A be an event of getting HEADS when a coin is tossed and probability of getting Heads when a coin is tossed is denoted and P(A) . Here , P(A) = 1/2 = 0.500 approximately . 

When we do it through Monte Carlo Simulations , we get the value of P(A) = 0.497 using the python code .

Analysis : The calculations done by Monte Carlo Simulations and in hand are approximately equal .