Probabilities and Statistics

Related lectures (30)

Page 1 of 3

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

Covers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.

Explores bias, variance, unbiased estimators, and confidence intervals in statistical estimation.

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

Explores linear regression estimation, hypothesis testing, and practical applications in statistics.

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

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

Explores fundamental theorems in probability and statistics, joint probability laws, and marginal distributions.

Covers the normal distribution, including its properties and calculations.

Explores linear regression estimation, linearity assumptions, and statistical tests in the context of model comparison.