1. The Monte Carlo algorithm estimates probabilities using random samples. 2. As sample numbers increase, results approximate true values. 3. This method is valuable when data is limited and simplified models are needed. 4. Large-sample calculations make computers essential for efficiency. 5. Monte Carlo simulations apply this method to model complex systems. 6. By running models with random var..

Estimation Guessing an unknown parameter from a sample Guessing the characteristics of a parameter from the statistics of a sample probability sample Probability distribution has parameters such as mean and variance that determine distribution. Sampling is repeated independently from a specific probability distribution. Sampling from the same parameter through sampling method Each observation is..