Probability Theory: Fundamentals and Calculations

Related lectures (29)

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Covers basic probability theory, conditional probability, independence, and Bayes' Theorem.

Explores variance, covariance, and practical applications in statistics and probability.

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

Explores independence and conditional probability in probability and statistics, with examples illustrating the concepts and practical applications.

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

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

Explores the strong convergence of random variables and the normal distribution approximation in probability and statistics.

Covers the basics of probability theory, random variables, joint probability, and inference.

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

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