Multiple linear regression uses two or more independent variables to predict a dependent variable. The result is an equation you can use to estimate future outcomes based on known data.

Multiple and Non-Linear Regression The variable you are trying to estimate is referred to as dependent, while the variable you use in the model to predict the dependent variable is called independent.

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 .

Using advanced techniques to make better predictions can help you stand out. Here's a step-by-step guide to learning how to do a regression analysis.

In recent columns we showed how linear regression can be used to predict a continuous dependent variable given other independent variables 1,2. When the dependent variable is categorical, a common ...

We will cover the computation of the regression equation and the analysis of variance table. We will also discuss S, R-Sq, R-Sq (adj), predicted values, confidence intervals, prediction intervals, and ...

Correlation analysis and interaction testing was done by multiple regression This showed that WHO stratification and stage had the highest correlation with both OS and DSS while Age, ... Regression ...