Lectures related to Mc Diarmid's Inequality

Covers the basics of statistical theory, including probability models, random variables, and sampling distributions.

Explores expected value in probability theory, including dice rolls and Bernoulli trials.

Random Variables: Expectation and Independence

Explores random variables, expectation, and independence in probability theory.

Probability and Random Variables: Key Concepts Explained

Explains key concepts in probability, including conditional probability, independence, and random variables, with practical examples to illustrate their applications.

Probability and Measure: Fundamentals and Applications

Covers fundamental concepts of probability theory and measure theory, including joint probabilities, random variables, and the central limit theorem.

Probability and Statistics

Covers fundamental concepts in probability and statistics, including distributions, properties, and expectations of random variables.

Expectation of a Random Variable

Defines the expectation for random variables, emphasizing the importance of absolute values.

Normal Distribution: Properties and Calculations

Covers the normal distribution, including its properties and calculations.