Covid and the Lockdown Effect

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Related lectures (30)

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COVID-19 Outbreak: Epidemiology and Mitigation

Explores the COVID-19 outbreak, its terminology, transmission, severity, and global impact, emphasizing the importance of mitigation strategies and digital epidemiology.

Probabilistic Models for Linear Regression

Covers the probabilistic model for linear regression and its applications in nuclear magnetic resonance and X-ray imaging.

Probability and Statistics: Basics and Applications

Covers fundamental concepts of probability and statistics, focusing on data analysis, graphical representation, and practical applications.

Logistic Regression: Model Interpretation and Comparison

Explores logistic regression model interpretation, parameter estimation, and model comparison using likelihood ratio tests.

Asymmetric Parametric Models: Extremal Coefficient

Explores asymmetric parametric models and the extremal coefficient in extreme value dependence.

Statistical Inference: Model Selection and Nuisance Parameters

Covers model selection, nuisance parameters, and higher-order inference methods in statistical inference.

Statistical Inference: Linear Models

Explores statistical inference for linear models, covering model fitting, parameter estimation, and variance decomposition.

Emerging Infectious Diseases

Explores the emergence of infectious diseases, global health issues, and the impact of pandemics on society.

Statistical Theory: Inference and Sufficiency

Explores statistical inference, sufficiency, and completeness, emphasizing the importance of sufficient statistics and the role of complete statistics in data reduction.

Probabilistic Linear Regression

Explores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.