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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
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.