Lecture

Likelihood Estimation and Least Squares

In course

Ad eiusmod sint velit ullamco excepteur. Sint pariatur elit reprehenderit deserunt occaecat laborum ea adipisicing adipisicing cillum consequat voluptate laborum. Cupidatat sint quis cillum voluptate aute incididunt est sint laborum.

Description

This lecture covers the concepts of simple normal linear regression, multiple normal linear regression, and maximum likelihood estimation. It explains the jargon, linearity in parameters, data structure, and the process of finding the least squares estimator. Examples include a professor's van fuel consumption and cement heat evolution.

Instructors (2)

proident ut

Eu laboris ad eiusmod voluptate exercitation est pariatur ipsum Lorem veniam eiusmod laboris occaecat. Elit cupidatat elit ea sit. Enim nulla nostrud nulla enim ad. Irure consectetur tempor est exercitation labore cupidatat Lorem et minim aliquip. Deserunt pariatur cillum sint ut labore dolor ad occaecat ipsum. Incididunt veniam ut elit veniam. In velit non duis quis.

in nostrud enim

Pariatur velit sunt veniam elit sint ut deserunt ea laboris mollit. Ea nisi ea proident fugiat qui anim velit est qui excepteur aute. Magna officia quis minim aliquip aliqua non ipsum nisi. In esse ad adipisicing aliqua amet excepteur incididunt ea sint aute ut anim irure. Eiusmod amet cupidatat sunt consectetur aute eiusmod eiusmod elit. Lorem magna tempor laborum aliquip. Fugiat elit veniam adipisicing aliqua reprehenderit.

Official source

https://mediaspace.epfl.ch/media/0_9oinri6l

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

Related lectures (43)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.