Precipitation and Hydrologic Design

Related lectures (29)

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

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

Explores maximum likelihood inference, comparing models based on likelihood ratios and demonstrating with a coin example.

Covers the fundamental concepts of statistics and their application in data science.

Explores maximum likelihood inference, model selection, and comparing models using likelihood ratios.

Explores copulas, simulation algorithms, fitting data with rank correlations, and GANs for image generation.

Explores bias, variance, and confidence intervals in parameter estimation using examples and distributions.

Introduces continuous random variables and their probability distributions, emphasizing their applications in statistics and data science.

Covers the basics of statistical theory, including probability models, random variables, and sampling distributions.

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