Probability and Statistics

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Related lectures (28)

Conditional Density and Expectation

Explores conditional density, expectations, and independence of random variables with practical examples.

Random Variables and Expected Value

Introduces random variables, probability distributions, and expected values through practical examples.

Conditional Probability: Prediction Decomposition

Explores conditional probability, Bayes' theorem, and prediction decomposition for informed decision-making.

Probability Distributions in Environmental Studies

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

Confidence Intervals: Definition and Estimation

Explains confidence intervals, parameter estimation methods, and the central limit theorem in statistical inference.

Probability and Statistics

Covers inequalities, joint Gaussian distribution, risk estimation, and classification method testing in probability and statistics.

Probability and Statistics

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

Probability and Statistics: Fundamentals

Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.

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