Markov Chains: Transience & Recurrence

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Probabilities and Statistics: Key Theorems and Applications

Discusses key statistical concepts, including sampling dangers, inequalities, and the Central Limit Theorem, with practical examples and applications.

Probability and Statistics

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

Probability and Statistics

Covers Simpson's paradox, probability distributions, and real-life examples 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.

Normal Distribution: Properties and Calculations

Covers the normal distribution, including its properties and calculations.

Probability and Statistics

Covers fundamental concepts in probability and statistics, including distributions, properties, and expectations of random variables.

Central Limit Theorem: Properties and Applications

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

Estimating Deviations

Covers Markov's and Chebyshev's Inequalities for random variables and probability distributions.

Probability Distributions in Environmental Studies

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

Probability Theory: Midterm Solutions

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