Great R: Level 1 by Michael Milton is a 2 hr video course which leads you from the basics of installing the R environment on your system to conducting basic analysis and presentation of your data. The course itself is delivered in a clear, concise manner and the author is very thorough in his approach. The pacing is very good and as a student, you are kept engaged and don’t tend to fall behind, nor feel that you wish that things could hurry along. This video course is a superb complement to written tutorials and reference manuals on the R environment.
The video and voice quality is great and the small tutorial chunks make it very easy to stop and come back. Additionally, the summaries at that start of each chunk build into this and immediately let you pick up where you let off. During the course, small pop-up summaries appear at critical points summarising a concept or providing a clear description of the command being executed. This greatly enables the play-along tutorial nature of the course.
The course is aimed at a student interested in discovering the power of R and demands no prior experience with R, statistics or a programming language. This does not mean that the assumption is that the user is absolutely naive and it is clear that some knowledge at different points is of advantage and plays well into the challenges set by the instructor.
I particularly like the teaching style of the author. He asks questions of you, the student, and sets up a series of periodic challenges to ensure that you are engaged and involved in the process…the best attempt to create an active learning environment as if the tutor was there sitting with you.
The overall scope of the module is appropriate. You are introduced to the environment and carry out a series of tasks that build on your familiarity with R. Milton takes you through a number of real-world exercises from start to finish. The file cycle allows for a thorough and grounded understanding.
One of the only small quibbles that I would note is the reliance on the external data source for the initial exercise. Although I was able to get the data from the UNData website, something was amiss with the CSV format and my screen then didn’t match that of the tutorial. In fact, what had happened was the data provider added an additional column consequently R seemed to have a little trouble with empty values in that column. This was solved with a quick tinker, but points to a long term issue. I do like that the author decided to use real-world data and to highlight the usefulness of R for working with public datasets, so am loathe to be over critical, but the challenge remains.
Much additional knowledge is conveyed both between discussion of types of arrays, and also the noting of smaller tips that the author has found that make working with the R environment more efficient.
I was very impressed with this course and would recommend it for anyone interested in delving into the world of R. In comparison to R in a Nutshell which I had previously reviewed, this course would make a very fine introduction and lead to picking up the further volume to expand on one’s knowledge of R. I would feel a lot more comfortable approaching the book after having gone through this video tutorial. All I can say now is bring on Great R: Level 2!
