Lecture

Estimation and Confidence Intervals

Description

This lecture covers the concepts of bias, variance, and mean squared error in the context of parameter estimation. It discusses unbiased estimators, maximum likelihood estimation, and confidence intervals. The instructor explains how to calculate confidence intervals for unknown and known variances, using normal and student distributions. Examples are provided to illustrate the application of these concepts in practice.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_r87d79xf

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics, Statistical hypothesis testing

Data analysis: Regression analysis

Mathematics

Probability theory: Topics in probability theory

Discrete mathematics: Graph theory

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