Today sees the publication of the 100th video in my series of How To... Programme in R. This video is about the exciting topic of multicollinearity - which can be a problem when building Multiple Linear Regression models. Here's a useful definition:
The term multicollinearity was first used by Ragnar Frisch. It describes a perfect or exact relationship between the regression exploratory variables. Linear regression analysis assumes that there is no perfect exact relationship among exploratory variables. In regression analysis, when this assumption is violated, the problem of Multicollinearity occurs (Statistics Solutions).
I am coming to the end of this series of R videos as there are only a few small topics left from modules that I covered in my teaching days at NCI. I have mostly kept up publishing one video every working day since mid-January, but this will soon stop as I run out of ideas, and the summer is here!
The number of views for each video continues to be low - only a handful have exceeded 100 views. The most popular ones so far deal with Linear Regression, and the Chi-squared Test for Independence. I know there is a lot of competition on YouTube for videos about R programming - so it was always going to be a tough start to getting views. Nevertheless, I have enjoyed making the videos, even though the pressure to keep up the one-a-day schedule was often hard and at the last minute.