I’ve been getting emails asking questions about my upcoming course on Forecasting using R. Here are some answers.
Do I need to use the Revolution Enterprise version of R, or can I use open-source R?
Open source R is fine. Revolution Analytics is organizing the course, but there is no requirement to use their software. I will be using open source R with Rstudio for demonstrating things in lectures.
Is the course free?
No. It costs $1000 to register for the course. The course is being run jointly by Revolution Analytics and Monash University. Most of the money will go to Monash University, and will fund a research assistant to help me with R package development. My R packages and my FPP textbook are free, but they do take time and resources to produce. This course is one way I am funding them.
Can I watch the lectures in my own time?
Provided you are registered, you will be able to log in and watch the lectures after the event. If you really want to, you can watch them repeatedly. This is particularly important for people in Eastern Europe or West Asia where the lectures are in the middle of the night.
Will I be able to ask questions?
Yes. The lectures are meant to be interactive, for those watching live. You can ask questions, interject, etc. I will also try to respond to questions after lectures, especially for those who cannot watch live.
If I’ve already read your books and blog, will I learn anything?
Probably. The course is based on my FPP book, so don’t expect me to cover things that aren’t discussed there. But most people find that they learn more through asking questions, seeing examples worked out, discussion, etc.
I have very little experience with R, short of playing around with Rcmdr. Is that ok?
It is worth brushing up on R if you don’t use it regularly. I will not be using Rcmdr. Instead, I will use Rstudio and we will be learning the relevant commands. A suitable intro is the tutorial at www.otexts.org/fpp/using-r.
If you feel that is not enough, try working through the tutorials at cyclismo.org.
Is there a reading list I can start on leading up to the lectures?
The course is not difficult from a mathematical/statistical perspective, and as long as you are not freaked out by a few equations you should be fine. If you wanted to brush up, go over multiple regression at an introductory level. A suitable background on this is chapter 5 of FPP, or chapter 3 of Pardoe’s Applied regression modeling. But you may have something else handy that would be equally suitable.
What else can I do to prepare?
If you really want to get a head start, try working through Michael Lundholm’s tutorial on R’s time series facilities.
I want to learn about forecasting xxxx. Is this course useful for this purpose?
The course is about time series forecasting. That is, when you want to forecast data collected regularly over time. So if you have annual profits, or monthly sales data, or weekly electricity demand, or daily passenger numbers, or something else collected regularly over time, then this course should be helpful. But if your forecasting problem does not fit into that paradigm, then it is probably not the course you need.