Multivariate Normal Distribution

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Variance and Covariance: Properties and Examples

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

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

Generating Functions: Properties and Applications

Explores generating functions, Laplace transform, and their role in probability distributions.

Independence and Covariance

Explores independence and covariance between random variables, discussing their implications and calculation methods.

Probability and Statistics

Covers probability, statistics, independence, covariance, correlation, and random variables.

Stochastic Models for Communications

Explores stochastic models for communications, covering mean, variance, characteristic functions, inequalities, various discrete and continuous random variables, and properties of different distributions.

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Covers random variables, expectation, and distributions in probability spaces.

Probability Distributions: Central Limit Theorem and Applications

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

Elements of Statistics: Exercises

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Principal Components: Properties & Applications

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