This Julia page is dedicated to the simulation and visualization of statistical concepts using the Julia programming language, a modern and high-performance tool designed for scientific computing. The objective of this page is to transform abstract theory into a concrete understanding through interactive and computationally powerful simulations. By leveraging Julia's expressive syntax and computational speed, we aim to create an environment that enables users to explore and internalise key mathematical foundations with clarity and precision. This page was started under the guidance of Dr. Amiya Ranjan Bhowmick, whose mentorship and academic vision laid the foundation for promoting intuitive and engaging learning through simulation-based understanding. His insights have been instrumental in shaping this platform into a meaningful and accessible educational resource. The examples and visualizations provided here are designed to promote deep comprehension by encouraging experimentation, discovery, and critical thinking. Rather than merely illustrating results, they invite learners to actively engage with the underlying structures and processes. Also sincerely thank Dr. Dipali Mestry for her valuable suggestion in creating this page.
Large Sample Approximations
Monte Carlo Integration
A Gentle Introduction to Statistical Computing using Julia
https://github.com/sujit016/A-Gentle-Introduction-to-Statistical-Computing-Using-Julia
Bayesian Computing with Julia: A Practical IntroductionÂ