Data science content navigation: recognition of common difficulties, part 1 | By Geremie Yeo | January 2025

Discover and correct erroneous concepts in online data science content to help you learn more effectively

The field of data science is vast and complex, often lacks clear answers. While I seek to solve doubts and learn new concepts online, I have encountered numerous low quality responses prone to errors, some surprisingly well received despite the fundamental misunderstandings. To help others navigate these difficulties, I am beginning a series to share mistakes found in the online content (some of them can be errors that I made in the past).

In this article, I will share 4 of these examples, along with a counterexample for each of them to refute those statements. For part 1, these examples will focus on the basic concepts of automatic learning and statistics.

The examples will be structured in this way

Mistake x : 

This prayer is incomplete, it should be

“In linear regression (LR), one of the assumptions is the objective and conditional on x It must be distributed normally “

To remember the definition of LR, although in its simplest form: The objective and is…