Testing: Likelihood Ratio Test

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Explores model checking and residuals in regression analysis, emphasizing the importance of diagnostics for ensuring model validity.

Explores hypothesis testing, emphasizing the likelihood ratio test and its applications in statistical analysis.

Introduces simple and multiple normal linear regression, and maximum likelihood estimation with practical examples.

Explores the impact of a binary covariate on binary responses using 2x2 tables.

Provides an overview of Generalized Linear Models, focusing on logistic and Poisson regression models, and their implementation in R.

Explores the Cramér-Rao bound, hypothesis testing, and optimality in statistical theory.

Explores Generalized Linear Models theory, including logistic and Poisson regression, model evaluation, and coefficient tests.

Explores latent variable models, EM algorithm, and Jensen's inequality in statistical modeling.

Introduces Discrete Choice Analysis, covering scale, depth, data collection, and statistical inference.

Covers the systematic derivation of a synchronization algorithm with a generalized likelihood test in wireless receivers.