Credible interval

Related lectures (32)

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Covers binary testing setups, observations, and proposals for next week's readings.

Covers the fundamentals of Bayesian estimation, focusing on the application of Bayes' Theorem in scalar estimation.

Covers the properties of continuous functions and explores inverse and injective functions with examples.

Covers criteria for estimating parameters, emphasizing the importance of consistency, bias, variance, and efficiency of estimators.

Covers conditional queries and joins in GIS, explaining operators and attribute selection based on conditions.

Covers the Monte Carlo method for generating realizations and unbiased estimators.

Explores optimal Bayesian inference, denoising, scalar estimation, and phase transitions.

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

Explores Gaussian processes, linear systems, transformations, and noise properties in multivariable control applications.

Discusses the maximal internal containing interval and its properties and solutions.