Maximum Likelihood EstimationCovers Maximum Likelihood Estimation in statistical inference, discussing MLE properties, examples, and uniqueness in exponential families.
Review Session: Module 1Introduces inferential statistics, covering sampling, central tendency, dispersion, histograms, z-scores, and the normal distribution.
Probabilities and StatisticsCovers fundamental concepts in probabilities and statistics, including linear regression, exploratory statistics, and the analysis of probabilities.
Latent Variable ModelsExplores latent variable models, EM algorithm, and Jensen's inequality in statistical modeling.
Monte-Carlo IntegrationCovers Monte-Carlo integration, simulation, and transforming draws from different distributions.
Special Families of ModelsExplores completeness, minimal sufficiency, and special statistical models, focusing on exponential and transformation families.
