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Related lectures (29)

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Basic Principles of Point Estimation

Explores the Method of Moments, Bias-Variance tradeoff, Consistency, Plug-In Principle, and Likelihood Principle in point estimation.

Stochastic Processes: Ergodicity

Covers the concept of ergodicity in continuous-time stochastic processes and the convergence of statistical properties over time.

Statistical Models: Sampling and Hypothesis Testing

Explores statistical models, sampling distributions, and hypothesis testing using real-world examples.

Semiconductor Devices II: Contact Resistance Modeling

Explores contact resistance modeling in semiconductor devices, focusing on gate voltage calculation and defect analysis.

Composite Elastic Constants

Covers the derivation of exact results for small strains in composite materials and the implications of experimental data outside these limits.

Bias, Variance, Consistency, EMV

Covers bias, variance, mean squared error, consistency, and maximum likelihood estimation in the Poisson model.

Eigenstate Thermalization Hypothesis

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

Applications of Quantum Science: Densities and Statistics

Covers the applications of densities and statistics in quantum science, focusing on binomial and Poisson distributions.

Quantile Normalization in Genomics

Explores quantile normalization in genomics, emphasizing data preparation, loading, filtering, and the significance of accurate gene expression analysis.

Point Estimation in Statistics

Explores point estimation in statistics, discussing bias, variance, mean squared error, and consistency of estimators.