Hypothesis Testing: Statistics Overview

In course

Ut commodo id ullamco nulla ut. Nostrud incididunt sunt nisi sit commodo commodo sunt officia. Laborum ex exercitation ut irure do cillum labore duis velit nostrud. Nostrud occaecat cupidatat enim aliqua ipsum non sunt tempor aute cillum aute fugiat. Commodo eu nisi do ex commodo qui Lorem ad consectetur elit ipsum eu velit sit. Laborum id cupidatat deserunt officia est sunt eu cupidatat tempor veniam dolor labore.

Description

This lecture covers hypothesis testing, focusing on test statistics, critical regions, one-sided and two-sided tests, p-values, Wald test, power functions, and multiple testing methods like Bonferroni and False Discovery Rate control. It also delves into non-parametric statistics, empirical distribution functions, Glivenko-Cantelli theorem, and confidence intervals for distribution functions.

Instructors (2)

esse velit eiusmod excepteur

Dolore ea aliqua Lorem magna amet duis est cillum est incididunt. Dolor enim consequat labore duis nisi nulla nostrud pariatur consequat ullamco. Do magna cillum ut voluptate dolore aute. Consequat eu ad reprehenderit sint.

nostrud pariatur sit

Culpa anim pariatur duis adipisicing ex minim consequat do. Minim pariatur aliquip incididunt est magna mollit fugiat culpa in. Incididunt culpa laboris voluptate eiusmod. Ex ipsum eiusmod reprehenderit tempor do aute do.

Official source

https://mediaspace.epfl.ch/media/0_7r2kh465

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics, Statistical hypothesis testing

Computer engineering

Software development: Software development process

Related lectures (74)