--- title: "Linear Regression-What, Why & How?" url: https://daily.dev/posts/linear-regression-what-why-how--97vtp10nb source_url: https://blog.gopenai.com/linear-regression-what-why-how-85c2e2d8cd2c type: article source: "GoPenAI" published: 2024-04-30T15:49:48.831Z updated: 2024-05-09T07:52:51.999Z tags: ["machine-learning", "data-analysis", "math", "statistics", "linear-regression"] reading_time: 2 upvotes: 7 comments: 0 language: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Linear Regression-What, Why & How? **[GoPenAI](https://daily.dev/sources/gopenai)** · 2 min read · 7 upvotes · 0 comments ## Summary Linear regression is a statistical method used to understand the relationship between variables and make predictions. It has assumptions about linearity, independence, homoscedasticity, normality of residuals, no multicollinearity, and no influential outliers. It is popular due to its simplicity, interpretability, and usefulness for modeling continuous outcomes. The algorithm involves calculating coefficients using mathematical equations and can be extended to multiple dimensions using matrix notation. Regularization techniques like L1 and L2 can be used to prevent overfitting. R2 score is a metric used to assess the model's fit to the data. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Don’t just attend KubeCon \+ CloudNativeCon, Merge Forward your experience\!](https://daily.dev/posts/don-t-just-attend-kubecon-cloudnativecon-merge-forward-your-experience--l0rpp73x8) · CNCF · 0 upvotes · 0 comments - [Announcing H2 2026 KCDs](https://daily.dev/posts/announcing-h2-2026-kcds-m96goajm1) · CNCF · 1 upvotes · 0 comments - [Two months of Open Community Groups](https://daily.dev/posts/two-months-of-open-community-groups-asf52zhbs) · CNCF · 0 upvotes · 0 comments --- Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#data-analysis](https://daily.dev/tags/data-analysis), [#math](https://daily.dev/tags/math), [#statistics](https://daily.dev/tags/statistics), [#linear-regression](https://daily.dev/tags/linear-regression) [View this post on daily.dev](https://daily.dev/posts/linear-regression-what-why-how--97vtp10nb)