The R programming language was designed by statisticians and was specialized for statistical computing. It is often regarded as the most important programming langauge for statistical analyses, but is also extremely useful for any type of data analysis. Many people want to learn R to gain skills for a career in data analysis.
Learning any programming language can be daunting for beginners, and there is no doubt that it will take a lot of time and lots of practice to develop skills for deep data analysis. Nevertheless, learning even the basics of R will allow beginners to perform simple data analysis such as visualizing data, make calculations, and performing statisical analysis.
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During my last two years as a Lecturer in the National College of Ireland I taught the module "Programming for Big Data" to students studying Data Analytics. I developed all my own scripts, course notes, R code, and sample data files - so I had built up quite a resource of R education material. I should point out that the R Cookbook (Long & Teetor, 2019) provided lots of inspiration and ideas for code. I am now launching a new series of YouTube videos based on my former module resources. I am also experimenting with YouTube's Premiere tool to announce the series at 16:00 tomorrow. I am also releasing the first five videos at this time, and hope to be able to chat to viewers after the launch.
All my R videos are short, mostly around 6-8 minutes long. Over the next few weeks I will release videos on a regular basis. At the time of writing this post, I have over 50 videos ready to go, but with a lot more planned.
While I have numbered the videos in sequence, it is not my intention to create a course in R programming - there are lots of free and paid for sites doing this. In fact, there is a lot of competition on-line for R education material. I have only modest hopes that my series will be successful. 99% of the people who watch my existing videos find them through a search for that particular topic. I expect the same for R videos.
Finally, I am making all my R code scripts, plus supporting files, available on my Github, where learners can view and download to try out - see https://github.com/eoloughlin/How-To-R.