Lecture

Linear Regression Essentials

In course

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Description

This lecture covers the essentials of linear regression, focusing on using multiple quantitative explanatory variables to predict a quantitative outcome. The instructor explains how to build a linear regression model, estimate parameters, interpret coefficients, and check model assumptions. The lecture also demonstrates how to apply linear regression in practice using a dataset about cars, discussing model fit, hypothesis testing, and model comparison. Additionally, it explores the concept of ANOVA and ANCOVA in the context of regression analysis.

Instructors (2)

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Official source

https://mediaspace.epfl.ch/media/0_f8f5yknz

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis

Statistical inference: Mathematical statistics, Statistical hypothesis testing

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