Bayesian probability

Related lectures (28)

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Explores conditional probability, Bayes' theorem, and prediction decomposition for informed decision-making.

Introduces statistics basics, including data analysis and probability theory, emphasizing central tendency, dispersion, and distribution shapes.

Covers the normal distribution, including its properties and calculations.

Explores joint random variables, conditional density, and independence in probability and statistics.

Introduces statistical analysis concepts like boxplot and normal distribution using real data examples.

Explores continuous random variables, density functions, joint variables, independence, and conditional densities.

Explores dynamic programming in finance, emphasizing optimal prediction strategies in market scenarios.

Explores independent events in probability theory and their applications in communication systems.

Covers fundamental concepts in probabilities and statistics, including linear regression, exploratory statistics, and the analysis of probabilities.

Covers the solutions to the midterm exam of a Probability Theory course, including calculations of probabilities and expectations.