Linear regression is a statistical technique used to describe a variable as a function of one or more predictor variables. Learn more with videos and examples.
To Reference this Page:Statistics Solutions. (2025). What is Linear Regression . Retrieved fromhere. Related Pages: Assumptions of a Linear Regression Take the course:Linear Regression Step Boldly to Completing your Research If you’re like others, you’ve invested a lot of time and money devel...
Linear regression is an analytics procedure that can generate predictions by using an easily interpreted mathematical formula.
Linear regression is a simple tool to study the mathematical relationship between two variables. Here’s how to try it for yourself. Written byPeter Grant Peter Grant Senior Scientific Engineering Associate at Lawrence Berkeley National LaboratoryPeter Grant is a building energy efficiency expert at La...
Linear regression is linear in that it guides the development of a function or model that fits a straight line -- called a linear regression line -- to a graph of the data. This line also minimizes the difference between a predicted value for the dependent variable given the corresponding in...
Linear regression is an important tool in analytics. The technique uses statistical calculations to plot a trend line in a set of data points. The trend line could be anything from the number of people diagnosed with skin cancer to the financial performance of a company. Linear regression shows...
As mentioned above, linear regression is a predictive modeling technique. It is used whenever there is a linear relation between the dependentand independent variables. Y = b0+ b1* x It isused to estimate exactlyhow much of y will change when x changes a certain amount. ...
Simple linear regression has two parameters: an intercept (c), which indicates the value that the label is when the feature is set to zero; and a slope (m), which indicates how much the label will increase for each one-point increase in the feature....
In general, a linear regression model can be a model of the formyi=β0+K∑k=1βkfk(Xi1,Xi2,⋯,Xip)+εi, i=1,⋯,n, where f (.) is a scalar-valued function of the independent variables, Xijs. The functions, f (X), might be in any form including nonlinear functions or...
What is Regression?: Regression is a statistical technique used to analyze the data by maintaining a relation between the dependent and independent variables.