Programming Background
2023-06-09
Note: this is for setup
knitr::opts_chunk$set(fig.path = "../images/")
##Programming Experience in R and Beyond
Everyone in this course had some programming experience coming in (due to the prerequisites). What are your thoughts on R vs whatever other software you’ve used? What functionality do you like about R? What parts do you miss about your other language? Do you consider R a difficult language to learn? (If you knew R prior to the course, describe your experience when first learning it.) Answer: R is similar to other software I’ve used such as Python (and specifically, it behaves pretty similarly to the pandas package in python). Like pandas, I love how easy it is to get statistics, analyses and plots/figures, without needing to create a billion four loops. I also like how stable it is. R is not at all a difficult language to learn; in fact, I had zero programming experience when I took my second intro to stats course which exclusively used R. We also used R almost exclusively when I was a statistics major in undergrad. During my intro course, it was kind of intimidating because I had no idea what some of the things were (what is a terminal? what’s markdown? and so on) but it was so functional and user-friendly that it didn’t really matter.
##Example R Markdown Output Here’s an example of how easy it is to create visualizations in R. For example, you can get some pretty sophisticated graphs using packages like ggplot2.
library(ggplot2)
gg <- ggplot(diamonds, aes(x=carat, y=price, color=cut)) + geom_point() + labs(title="Scatterplot", x="Carat", y="Price")
print(gg)
