In frank113/cmu202: Necessary Packages and Data for 36-202 at Carnegie Mellon University

## library(R202)
## library(ggplot2)

## load("../R/sysdata.rda")
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.align = "center",
  warning = FALSE,
  message = FALSE,
  echo = FALSE,
  fig.width = 7,
  height = 6
)

axis.size <- 20
font <- "Times"

Introduction to R Studio

The R Programming Langauge

R is a FREE programming language / environment that is often used for statistical analysis and graphing. R is an amazing tool that is widely used by data scientists, researchers, and professionals from all fields. It has built-in statistical tools that help facilitate both qualitative and quantitative analysis of data. It is open-source and helps facilitate reproducible research. You can read more about it here.

Developed in 1993 by Professors from the University of Auckland, R is one of the most commonly used programming languages for data science. Ranked at the 10th most popular programming language (see the Tiobe Index); R is a vital skill for most data scientists.

On a side note, the name R comes not from a grand scheme of meaning; the two scientists who developed the language both have names that begin with R.

RStudio

R Studio is known as an integrated development environment (IDE), a tool that contains all resources to develop R at any level. The layout of R studio is given as follows:

You will see four panes within the R Studio window.

• In the upper left pane we have the .Rmd file that we are working on.

• In the upper right pane we have our current environment which includes any loaded data, variables, or functions.

• In the lower right pane we will view plots, install packages, and get help on functions.

• In the lower left pane we have the Console. This is where you will execute code. This also acts like a computer.

frank113/cmu202 documentation built on July 17, 2020, 9:31 p.m.