Monte Carlo Methods: Using Random Sampling to Solve Complex Numerical Problems in Inference
					Introduction: When Uncertainty Becomes the Artist’s Brush Imagine standing before a vast canvas with no clear lines—just probabilities swirling like mist. Instead of a paintbrush, you hold randomness itself. Every stroke, every drop of chance, slowly reveals a pattern—a masterpiece shaped not by certainty, but by repetition and probability. That’s what Monte Carlo methods do. They transform randomness into precision, turning uncertainty into a reliable ally for solving the most complex problems in inference. From estimating the value of π to predicting financial risks and Bayesian posterior distributions, Monte Carlo simulations have become the invisible artisans behind modern computational science....				
				
			
 
		 
		 
		 
		 
		 
		 
		 
		 
		