Error Estimation in LHS

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Explores bias, variance, unbiased estimators, and confidence intervals in statistical estimation.

Explores bias, variance, and confidence intervals in parameter estimation using examples and distributions.

Explores estimating parameters through confidence intervals in linear regression and statistics.

Explores the distribution theory of least squares estimators in a Gaussian linear model, focusing on precision and confidence intervals construction.

Explains confidence intervals, parameter estimation methods, and the central limit theorem in statistical inference.

Covers hypothesis testing, confidence intervals, data distributions, and statistical significance in data analysis.

Provides an overview of basic probability theory, ANOVA, t-tests, central limit theorem, metrics, confidence intervals, and non-parametric tests.