Monte Carlo Simulation | Solved Example | Solving Integrals скачать в хорошем качестве

Monte Carlo Simulation | Solved Example | Solving Integrals

In this video, you will learn how to estimate definite integrals using Monte Carlo simulation, with a focus on evaluating the Gaussian integral of the form ∫ e^(-x²) dx over a symmetric interval. The method is explained step by step, including how random sampling is used, why the technique works statistically, and how to implement it in Python. This tutorial also highlights key assumptions, potential pitfalls, and ways to improve accuracy. By the end of the video, you will have a clear understanding of how Monte Carlo integration works, its practical applications in simulations and computational mathematics, and how to apply it to other functions and intervals. If you are facing any issues do let me know in the comment section below, I am here to help ❤️ If you found this video useful then please consider subscribing to my channel 🙏 Chapters in the video: 0:00 Introduction 0:33 Problem Statement 01:04 Introduction 02:50 Real World examples 03:51 Applying Monte Carlo Simulation 07:30 Key Learnings 08:05 Common Mistakes to Avoid 08:55 Enhancements on MCS 11:20 Conclusion Background Music Credits (in order of use) Outro Music Credit: Spirit by Sappheiros: "Spirit by Sappheiros" is under a Creative Commons ( cc-by ) license Music promoted by BreakingCopyright: https://bit.ly/sappheiros-spirit