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Linear Models: Estimation and Inference

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Related lectures (36)

Generalized Linear Models: A Brief Review Log in to Mediaspace to watch this video

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

Model Checking and Residuals Log in to Mediaspace to watch this video

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

Modern Regression: Statistical Models and Data Analysis Log in to Mediaspace to watch this video

Introduces regression analysis, covering linear and nonlinear models, Poisson regression, and failure time analysis using various datasets.

Regression Methods: Model Building and Diagnostics Log in to Mediaspace to watch this video

Explores regression methods, covering model building, diagnostics, inference, and analysis of variance.

Linear Regression: Model Adjustment and Parameter Estimation Log in to Mediaspace to watch this video

Explains the decomposition of total sum of squares, model adjustment, and parameter estimation in linear regression.

Linear Regression: Ozone Data Analysis Log in to Mediaspace to watch this video

Explores linear regression analysis of ozone data using statistical models.

Linear Models for Classification: Logistic Regression and SVM Log in to Mediaspace to watch this video

Covers linear models for classification, focusing on logistic regression and support vector machines.

Regularization in Machine Learning Log in to Mediaspace to watch this video

Introduces regularization techniques to prevent overfitting in machine learning models.

Inference and Mixed Models Log in to Mediaspace to watch this video

Covers point estimation, confidence intervals, and hypothesis testing for smooth functions using mixed models and spline smoothing.

Statistical Theory: Inference and Optimality Log in to Mediaspace to watch this video

Explores constructing confidence regions, inverting hypothesis tests, and the pivotal method, emphasizing the importance of likelihood methods in statistical inference.

Linear and Quadratic Models of Scheffé Log in to Mediaspace to watch this video

Explores linear and quadratic models of Scheffé in mixing plans and ternary schemes, emphasizing constraints and representations.

Linear Mixed Model Log in to Mediaspace to watch this video

Covers the linear mixed model, including fixed and random effects, estimation, and inference techniques.

Likelihood Ratio Tests: Optimality and Extensions Log in to Mediaspace to watch this video

Covers Likelihood Ratio Tests, their optimality, and extensions in hypothesis testing, including Wilks' Theorem and the relationship with Confidence Intervals.

Heteroskedasticity: Ch. 4a Log in to Mediaspace to watch this video

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Estimating R: Example 100 Log in to Mediaspace to watch this video

Explores correlation limitations, probability, random variables, and statistical inference using a ball-drawing example.

Data Representation: PCA Log in to Mediaspace to watch this video

Covers data representation using PCA for dimensionality reduction, focusing on signal preservation and noise removal.

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