Hello, R — vectors are everywhere

R is the lingua franca of academic statistics, a major language in applied research and policy work, and the home of two ecosystems that no other language matches: the tidyverse for data manipulation and ggplot2 for graphics. If you do econometric research, R will be the tool you reach for at least half the time.

Vector-first by default

R was designed for statistics from the ground up. Its primary data type is the vector, not the scalar. Operations work element-wise without ceremony. This makes R unusually concise for the kinds of computations a statistician does — and unusually quirky for programmers coming from other languages.

x <- c(1, 2, 3, 4, 5)
x * 2          # 2 4 6 8 10
mean(x)        # 3
x > 3          # FALSE FALSE FALSE TRUE TRUE

The assignment arrow

R uses <- (an arrow) for assignment, with = also accepted but considered less idiomatic. The arrow makes it visually obvious which way data is flowing. RStudio (the IDE most R users use) has a keyboard shortcut: Alt+- inserts <- with surrounding spaces.

Reading the help pages

Type ?function_name in the R console to open the help page. Every function in R has a structured help page with: arguments, value, examples, references. The examples at the bottom are usually the fastest way to figure out what a function does.

?mean
?lm
help("summary")

WebR — running R in your browser

The practice environment to the right of this course runs real R compiled to WebAssembly via WebR. The tidyverse and ggplot2 are pre-loaded. Three Kenyan datasets — bankrates, pension, mpesa — are loaded as data frames so you can practise on real data immediately.