In statistics, linear regression is a model that estimates the relationship between a scalar response (dependent variable) and one or more explanatory variables (regressor or independent variable).

In this post, you’ll learn how to interprete linear regression with an example, about the linear formula, how it finds the coefficient estimates, and its assumptions.

Jan 12, 2026 · The goal of linear regression is to find a straight line that minimizes the error (the difference) between the observed data points and the predicted values. This line helps us predict the …

Dec 13, 2025 · Linear regression, in statistics, a process for determining a line that best represents the general trend of a data set. The simplest form of linear regression involves two variables: y being the …

Jun 5, 2025 · What is Linear Regression? Linear regression is a statistical method used to model the relationship between a dependent variable (also known as the response variable or outcome …

This form of analysis estimates the coefficients of the linear equation, involving one or more independent variables that best predict the value of the dependent variable. Linear regression fits a straight line or …

Sep 28, 2024 · Learn simple linear regression. Master the model equation, understand key assumptions and diagnostics, and learn how to interpret the results effectively.

Oct 13, 2025 · You can delve into the intricacies of linear regression throughout this article, including its definition, various types of linear regression, and how different careers utilize this statistical tool.

Linear Regression is a simple and powerful model for predicting a numeric response from a set of one or more independent variables. This article will focus mostly on how the method is used in machine …

Learn the fundamentals of linear regression, with a step-by-step derivation of the model and a practical example. This article covers basic concepts and includes an example to show how linear regression …