Variance

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Related lectures (32)

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Estimation Methods in Probability and Statistics

Discusses estimation methods in probability and statistics, focusing on maximum likelihood estimation and confidence intervals.

Convergence in Probability

Explores convergence in probability, concentration inequalities, laws of large numbers, and properties of distributions.

Global Sensitivity Analysis in Stochastic Systems

On Variance-Based Sensitivity Analysis for Stochastic Systems covers the impact of parameters uncertainty and sensitivity indices in stochastic models.

Heteroscedasticity: Modeling Scale Parameters

Covers heteroscedasticity in nonlinear specifications, modeling scale parameters across different groups in the population.

Estimator of Variance

Explores variance estimation, creating personal estimators, correcting bias, and understanding Mean Square Error in statistical analysis.

Estimating Relaxation Time: Variance and Chains

Covers the estimation of relaxation time in chains and the importance of sample sizes.

Regression Methods: Model Building and Diagnostics

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

Advanced Probability: Summary

Covers random variables, sample spaces, probability distributions, functions, expected value, variance, and estimations.

Regression: Simple and Multiple Linear

Covers simple and multiple linear regression, including least squares estimation and model diagnostics.

Stochastic Simulations: Ergodicity and Estimators

Explores geometric ergodicity in Markov chains and estimators' bias and variance, highlighting efficiency loss quantification.