Linear regression (also called simple regression) is one of the most common techniques of regression analysis. Multiple regression is a broader class of regression analysis, which encompasses both ...

Linear regression is a statistical method used to understand the relationship between an outcome variable and one or more explanatory variables. It works by fitting a regression line through the ...

Here's how to run both simple and multiple linear regression in Google Sheets using the built-in LINEST function. No add-ons or coding required.

Multiple Linear Regression: Multiple linear regression describes the correlation between two or more independent variables and a dependent variable, also using a straight regression line.

Course Topics In this short course we will cover how to analyze simple and multiple linear regression models. You will learn concepts in linear regression such as: 1) How to use the F-test to ...

Functional linear regression is a useful extension of simple linear regression and has been investigated by many researchers. However, the functional variable selection problem when multiple ...

Jerome H. Klotz, UPDATING SIMPLE LINEAR REGRESSION, Statistica Sinica, Vol. 5, No. 1 (January 1995), pp. 399-403 ...

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 ...

Linear Regression vs. Multiple Regression Example Consider an analyst who wishes to establish a relationship between the daily change in a company's stock prices and daily changes in trading volume.