Extreme Problems in Diophantine Approximation and Dynamics

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

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

Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.

Covers properties and calculations related to the normal distribution, including probabilities and quantiles.

Explores continuous random variables and their properties, including support and cumulative distribution functions.

Covers probability distributions, moments, and continuous random variables.

Explores probability convergence, discussing conditions for random variable sequences to converge and the uniqueness of convergence.

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

Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.

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