Probability and Statistics: Fundamentals

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Related lectures (30)

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Conditional Probability Distributions

Covers conditional probability distributions and introduces the concept of conditional expected value.

Normal Distribution: Properties and Calculations

Covers the normal distribution, including its properties and calculations.

Introduction to Inference

Covers the basics of probability theory, random variables, joint probability, and inference.

Probability and Statistics

Covers p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.

Modes of Convergence of Random Variables

Covers the modes of convergence of random variables and the Central Limit Theorem, discussing implications and approximations.

Probability and Random Variables: Key Concepts Explained

Explains key concepts in probability, including conditional probability, independence, and random variables, with practical examples to illustrate their applications.

Probability Distributions in Environmental Studies

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

Linear Combinations: Moment-Generating Functions

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

Conditional Density and Expectation

Covers conditional density, independence of random variables, expectation, and variance calculation.

Independence and Covariance

Explores independence and covariance between random variables, discussing their implications and calculation methods.