Credit: Technology Networks. An additional assumption for multiple linear regression is that of no collinearity between the explanatory variables, meaning they should not be highly correlated with ...

In this module, we will introduce the basic conceptual framework for statistical modeling in general, and linear statistical models in particular. In this module, we will learn how to fit linear ...

We’ll extend our simple linear model to take into account some of the other variables in the marketing data in this exercise. We’ll start by adding in facebook to our first simple linear model ...

Investopedia / Yurle Villegas A variance inflation factor (VIF) is a measure of the amount of multicollinearity in regression analysis ... exists when there is a linear relationship, or ...

Statistical data analysis in R covering the following topics: Simple and multiple linear regression, Model diagnostics, Detection of outliers, Multicollinearity, Introduction to GLMs. This course will ...

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 ...

In this workshop we look at where we have more than one predictor in our linear model. Start by downloading labC05.Rmd and load it into RStudio. Any text in italics reminds you that you need to have a ...