Frequentist inference

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Related lectures (32)

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Assumption-lean Inference: Generalised Linear Model Parameters

Explores assumption-lean inference for statistical estimands in generalised linear models, emphasizing robust and generic approaches.

Maximum Likelihood: Inference and Model Comparison

Explores maximum likelihood inference, model selection, and comparing models using likelihood ratios.

Bayesian Inference: Precision in Gaussian Model

Explores Bayesian inference for precision in the Gaussian model with known mean, using a Gamma prior and discussing subjective vs objective priors.

Optimization-Based Uncertainty Quantification

Explores optimization-based uncertainty quantification for ill-posed inverse problems in the physical sciences, focusing on regularization methods and interval constructions.

Estimating R: Example 100

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

Statistical Estimation: Maximum Likelihood

Explores Maximum Likelihood Estimation properties, challenges, and alternative methods in statistical inference.

Nuclear Power Safety Concerns

Covers nuclear power safety concerns post-Fukushima, extreme weather impact, and financial risk estimation using extreme value theory.

Bias and Variance in Estimation

Discusses bias and variance in statistical estimation, exploring the trade-off between accuracy and variability.

Hypothesis Testing: Q-Q Plots and Non-Parametric Tests

Covers hypothesis testing, Q-Q plots, and non-parametric tests in statistics.

Statistical Inference: Approximate Critical Values and Confidence Intervals

Covers the construction of confidence intervals and approximate critical values in statistical inference.