Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

You perform a multiple linear regression analysis when you have more than one explanatory variable for consideration in your model. You can write the multiple linear regression equation for a model ...

Linear regression captures the relationship between two variables—for example, the relationship between the daily change in a company's stock prices and the daily change in trading volume.

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Compared to standard linear ...

Multiple linear regression is widely used in the real estate industry to estimate housing prices. Instead of relying on a single factor, it considers several variables simultaneously.

One common problem in the use of multiple linear or logistic regression when analysing clinical data is the occurrence of explanatory variables (covariates) which are not independent, ie ...

Linear forecasting models can be used in both types of forecasting methods. In the case of causal methods, the causal model may consist of a linear regression with several explanatory variables.