R is the first programming language I have had the oppourtunity to get deep experience in. I had some experience with R before starting the Master’s program from taking Dataquest lessons. I found these lessons very helpful as they provided short readings followed by short exercises, so I quickly got used to writing code to solve problems. They also had lessons on Python, and I found the two languages about equal in difficulty. Since starting the statistics program, I have nearly always had R open on my computer to work on assignments and projects. It’s the first language I really feel comfortable using, and I did not find it too difficult to learn.

My favorite things about R are the packages and flexibility. It’s wonderful that you can do almost anything you want fairly painlessly with R packages. I never thought I would be good at coding, but once I discovered that R is essentially a big fancy calculator, it helped me grasp the ideas much more easily. I haven’t spent enough time in Python to make a meaningful comparison between the two languages, but I would like to spend some more time learning it as I know it is widely used in industry. I have gotten some experience using SAS, however, and after having taken the SAS course, I prefer R for most data analysis.

SAS is excellent for performing statistical operations and the proc steps lead to very clean and intuitive code, but R is more flexible. R does a lot of the heavy lifting for you, especially when reading in data and setting attributes, compared to SAS where you have to do it manually. I prefer SAS for statistical operations such as ANOVA or GLMs, because it gives you a lot of very nicely formatted and relevant output, along with interaction plots and such. R, on the other hand, is easier to use for data manipulation and exploratory data analysis. You have much more flexibility with the dataframes by using the tidyverse, and you can generally get your data into a usable format in a few lines of code. I also prefer creating charts and graphs in R. Base R plotting will get you plotting your data in seconds, but you can learn how to make very appealing visuals with ggplot.

Overall, I’m overcoming the learning curve in R and I expect that my understanding of the logic behind what I’m doing will make learning my next programming language even easier.