Generalized Linear Models

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Related lectures (30)

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Sampling Theory: Statistics for Mathematicians

Covers the theory of sampling, focusing on statistics for mathematicians.

Normal Distribution: Properties and Calculations

Covers the normal distribution, including its properties and calculations.

Probability Distributions

Covers various probability distributions and their applications in real-world scenarios.

Eigenstate Thermalization Hypothesis

Explores the Eigenstate Thermalization Hypothesis in quantum systems, emphasizing the random matrix theory and the behavior of observables in thermal equilibrium.

Continuous Random Variables

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

Common Distributions: Moments and MGFs

Covers common distributions, moment generating functions, and covariance matrices in statistics for data science.

Descriptive Statistics: Hypothesis Testing

Introduces descriptive statistics, hypothesis testing, p-values, and confidence intervals, emphasizing their importance in data analysis.

Elementary Distributions Factsheet

Covers elementary distributions like Bernoulli, Binomial, Geometric, Negative Binomial, Poisson, and Multinomial.

Probabilities and Statistics

Covers fundamental concepts in probabilities and statistics, including linear regression, exploratory statistics, and the analysis of probabilities.

Multivariate Statistics: Normal Distribution

Covers the multivariate normal distribution, properties, and sampling methods.