The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9. I will start with a ...

Some key advantages of linear regression are that it can be used to predict values of the outcome variable and incorporate more than one explanatory variable. The linear regression equation is perhaps ...

A multiple regression formula has multiple slopes (one for each variable) and one y-intercept. It is interpreted the same as a simple linear regression formula—except there are multiple ...

we can develop a regression equation to forecast or predict the variable we desire. Below is the formula for a simple linear regression. The "y" is the value we are trying to forecast, the "b" is ...

There are approximately a dozen common regression techniques. The most basic technique is called linear regression, or sometimes multiple linear regression ... the prediction equation is y' = (w0 * x0 ...

Now that you've got a good sense of how to "speak" R, let's use it with linear regression to make distinctive predictions. The R system has three components: a scripting language, an interactive ...