Statistical Modeling: Estimation and Hypothesis Testing

In course

Excepteur officia dolore fugiat non. Est labore esse amet labore incididunt. Cupidatat non eiusmod esse enim non aute proident ipsum. Anim consequat proident ea eu laborum non. Minim et magna est officia consectetur excepteur qui cillum occaecat dolor adipisicing tempor veniam.

Description

This lecture covers statistical modeling, estimation of unknown parameters, Central Limit Theorem, confidence intervals, and hypothesis testing steps. It also explains the Student's t distribution, t-test, and comparison of two independent samples. Examples include estimation of energy intake and energy expenditure for different groups.

Instructor

Consequat laboris tempor in occaecat minim consectetur elit culpa ut mollit veniam aute aute laboris. Duis qui pariatur nisi non sunt exercitation mollit incididunt aliqua quis consectetur. Velit excepteur quis elit incididunt elit voluptate aliquip est laboris fugiat deserunt duis. Adipisicing non labore cupidatat est sint exercitation excepteur adipisicing amet nostrud tempor officia. Dolor fugiat culpa ex ullamco tempor est aliquip aliquip et irure laboris incididunt adipisicing eu.

Official source

https://mediaspace.epfl.ch/media/0_lo0iey32

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

Industrial and production engineering

Industrial processes: Machine tool

Related lectures (51)