Estimating Random Variables

Related lectures (30)

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Explores the Central Limit Theorem, covariance, correlation, joint random variables, quantiles, and the law of large numbers.

Introduces the basics of probability models, covering random variables, distributions, and statistical estimation.

Delves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.

Explores quantiles, sampling, and histogram density for understanding distributions and constructing confidence intervals.

Explains moments, expectation, variance, and quantiles in probability distributions with examples like Poisson and exponential distributions.

Covers the calculation of expectation and variance for different types of random variables, including discrete and continuous ones.

Covers random variables, probability functions, expectations, variances, and joint distributions.

Introduces probability theory, random variables, and distributions, with a focus on their applications in atomic diffusion.

Covers the theory of Brownian motion, diffusion, and random walks, with a focus on Einstein's theory for one-dimensional motion.

Covers random variables, sample spaces, probability distributions, functions, expected value, variance, and estimations.