Probability Distributions: Basics and Properties

Related lectures (30)

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Covers statistical concepts like probability, estimation, hypothesis testing, and confidence intervals for mathematicians.

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

Introduces probability mass functions for discrete random variables and various distributions, emphasizing the calculation of expectations.

Covers the normal distribution, including its properties and calculations.

Covers the concept of variance for random variables and introduces calculation rules.

Covers stochastic models for communications, focusing on random variables, Markov chains, Poisson processes, and probability calculations.

Introduces random variables, probability density functions, and Gaussian distribution in statistics.

Covers the fundamental concepts of probability theory and random variables.

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

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