Simple linear regression examines the relationship between one outcome variable and one explanatory variable only. However, linear regression can be readily extended to include two or more explanatory ...

The four most common types of linear regression are simple, multiple, and polynomial. Understanding their differences can help you determine which approach best suits your needs: ...

Multiple Linear Regression In linear regression, when there's just a single independent variable, the analysis is sometimes called simple linear regression to distinguish the analysis from situations ...

Simple linear regression is commonly used in forecasting and financial analysis—for a company to tell how a change in the GDP could affect sales, for example. Microsoft Excel and other software ...

Nonlinear regression is a form of regression analysis in which data is fit to a model and then expressed as a mathematical function. Simple linear regression relates two variables (X and Y) with a ...

This Month Published: 01 December 2015 Points of Significance Multiple linear regression Martin Krzywinski & Naomi Altman Nature Methods 12, 1103–1104 (2015) Cite this article ...

Course TopicsLinear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the ...