Lectures related to Probabilistic Information Retrieval

Covers fundamental concepts of probability and statistics, focusing on data analysis, graphical representation, and practical applications.

Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.

Delves into probability, statistics, random experiments, and statistical inference, with practical examples and insights.

Covers the normal distribution, including its properties and calculations.

Covers Simpson's paradox, probability distributions, and real-life examples in probability and statistics.

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

Explores the estimation of expectation for discrete random variables, emphasizing its importance in probability theory.

Introduces key statistical concepts like probability, random variables, and correlation, with examples and explanations.