Ronald Fisher

Formal sciences
Statistics
Statistical inference
Statistical hypothesis testing

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Related lectures (26)

Page 2 of 3

Confidence Intervals and Pivotal Quantities

Explores pivotal quantities in statistics and their role in constructing confidence intervals and hypothesis tests.

Linear Binary Classification

Covers the extension of the 0-1 loss to real-valued score functions and logistic regression.

Maximum Likelihood, MSE, Fisher Information, Cramér-Rao Bound

Explains maximum likelihood estimation, MSE, Fisher information, and Cramér-Rao bound in statistical inference.

Statistical Theory: Cramér-Rao Bound & Hypothesis Testing

Explores the Cramér-Rao bound, hypothesis testing, and optimality in statistical theory.

Statistical Theory: Inference and Sufficiency

Explores statistical inference, sufficiency, and completeness, emphasizing the importance of sufficient statistics and the role of complete statistics in data reduction.

Variance and Independent Random Variables

Covers variance, independent random variables, and their properties, including examples and proofs.

Parameter Estimation & Fisher Information

Covers parameter estimation, Fisher information, unbiased estimator, and exponential distributions.

Intro to Quantum Sensing: Parameter Estimation and Fisher Information

Introduces Fisher Information for parameter estimation based on collected data.

Maximum Likelihood Estimation

Introduces maximum likelihood estimation for statistical parameter estimation, covering bias, variance, and mean squared error.

Maximum Likelihood Estimation

Covers Maximum Likelihood Estimation in statistical inference, discussing MLE properties, examples, and uniqueness in exponential families.