Statistics: Random Variables and Probability Density Functions

Related lectures (30)

Page 2 of 3

Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.

Covers the fundamental concepts of probability theory and random variables.

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

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

Covers continuous random variables, probability density functions, and distributions, with practical examples.

Covers the solutions to the midterm exam of a Probability Theory course, including calculations of probabilities and expectations.

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

Explores moment-generating functions, linear combinations, and normality of random variables.

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.