Lectures related to Random Walks and Moran Process

Covers amplitude shift keying and various data analysis techniques using Jupyter Notebooks.

Explores the Central Limit Theorem, covariance, correlation, joint random variables, quantiles, and the law of large numbers.

Covers concentration inequalities and sampling methods for estimating unknown distributions, with a focus on population infection rates.

Covers probability, statistics, independence, covariance, correlation, and random variables.

Explores confidence intervals, hypothesis testing, and decision-making using test statistics and p-values.

Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.

Covers the algorithm to simulate molecule reactions using random numbers.

Explores fundamental theorems in probability and statistics, joint probability laws, and marginal distributions.