Intro to Probability
Monte Carlo methods are a set of computational algorithms that rely on repeated random sampling to obtain numerical results. They are particularly useful in situations where it is difficult to predict an outcome using traditional analytical methods, such as integrating complex functions or simulating random variables. These methods can help estimate probabilities, including those associated with probability density functions, and they also play a significant role in understanding distributions like the binomial distribution by simulating various scenarios.
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