I started digging into R around August 2016 mostly because at that time I was taking the course - "Statistics and Probabilty" (MAT3103) and I was curious to get a slight taste of actual statistical computations done in research or real world data analysis.
This note mostly contains things I found amazing about R and also the things I disliked about it. A the same time this will also serve as a future reference for myself. Please note that I only had a brief intereaction with the language and barely scratched the surface. And this is not another Python vs. R thing, since I have little or no experience with Python (at this time) so, I won't be able to do justice in comparing them.
This is just my personal take on R
- R-card
- Sample Data Sets
- Nothing can get any simpler than read.csv()
- Think mathematically/statistically
- Understanding the mathematical/statistical formulas and their parameters is important. The better your concepts are clear about various statistical models the faster you will catch up with R
- If you are the math-geeky type , R is a perfect fit