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 …

Jan 22, 2026 · 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 …

Sep 28, 2024 · Every story starts somewhere, and for the data analyst or data scientist, the start of the story is often simple linear regression. Indeed, simple linear regression is perhaps the most …

Linear regression analysis is used to predict the value of a variable based on the value of another variable. The variable you want to predict is called the dependent variable. The variable you are …