3 Ways Linear Models Can Lead to Erroneous Conclusions
Last Updated on July 20, 2023 by Editorial Team
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Originally published on Towards AI.
In this article, I will share 3 ways in which linear models can lead to erroneous conclusions. The focus will be on fitting linear models to simulated data and checking whether the resultant estimates are consistent with the simulation.
This article is based on the content of [1].
The code to reproduce the results described in this article can be found in this notebook.
Let Y be the thing we would like to model. Suppose we know that Y is defined by a vector of variables X as Y = β X, where β is a vector of parameters, one for each variable… Read the full blog for free on Medium.
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