Basics of Risk Analysis and Management

Related lectures (30)

Page 2 of 3

Covers the normal distribution, including its properties and calculations.

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

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

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

Covers fundamental statistics concepts, including estimation theory, distributions, and the law of large numbers, with practical examples.

Explores advanced probabilities, random variables, and expected values, with practical examples and quizzes to reinforce learning.

Discusses probability distributions and the Central Limit Theorem, emphasizing their importance in data science and statistical analysis.

Explores statistical models, families of distributions, transformations, and their applications in probability theory.

Explores various continuous probability distributions and expectation of random variables.

Covers probability distributions, moments, and continuous random variables.