Lecture: ShannonCovers the basics of information theory, focusing on Shannon's setting and channel transmission.
Probability and StatisticsIntroduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.
Maximum Likelihood InferenceExplores maximum likelihood inference, comparing models based on likelihood ratios and demonstrating with a coin example.
Detection & EstimationCovers binary classification, hypothesis testing, likelihood ratio tests, and decision rules.
Probability and StatisticsDelves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.
Discrete Choice AnalysisIntroduces Discrete Choice Analysis, covering scale, depth, data collection, and statistical inference.
