Post by Madhan Kumar Narri

Monte Carlo Estimation of π Using Buffon's Needle 🎯: A Statistical Analysis A classic Geometrical Probability problem solved by Monte Carlo Simulation to estimate π The experiment involves randomly dropping a needle of length l onto a plane containing parallel lines spaced t units apart (where l≤t).  The formula used => P = (2*l) / (π*t) Estimated π using Monte Carlo Simulation 📈 Performed Convergence Analysis to study the behavior of the estimator 📊 Conducted Variance Analysis through repeated simulations 📉 Evaluated the estimation accuracy using Error Analysis ⚡ Analyzed Time Complexity and measured execution performance 📌 Visualized the results using NumPy and Matplotlib As the number of Monte Carlo simulations increased, the estimated value of π converged towards the true value of π, illustrating the Law of Large Numbers. What's fascinating is that we're estimating an almost accurate value of π even though they are no real circles involved . The complete project, including the implementation, source code, analysis, and visualizations are available on GitHub https://lnkd.in/gRczJXBy I'd appreciate any feedback or suggestions for improvement. #Python #MonteCarlo #Probability #Statistics #QuantitativeFinance #QuantResearch #DataScience #NumPy #Matplotlib #AlgorithmAnalysis #BuffonsNeedle #MachineLearning #GitHub