• Discover what R is
• Understand the advantages of R
• Find your way around RStudio
• Get to know the basic R building blocks of R

• R is a free software environment for statistical computing and graphics
• It works with a wide variety of platforms

1. You can do anything in R.
2. R facilitates reproducible science
3. Long term gain from upfront investment

• RStudio helps you write in R by:
  • sending your written code to R
  • ‘syntax-highlighting’
  • keeping a history of your actions
  • giving you tools to fix your code when it doesn’t work (debugging)

• The 3 main building block of R are:
  • names
  • data: vectors and data frames
  • functions

• We use the <- assignment operator to assign a name.

answer <- 42
msg <- "Hello World!"
answer

## [1] 42

msg

## [1] "Hello World!"

• You can perform math!

x <- 2
y <- 4

x + y

## [1] 6

x * y

## [1] 8

x / y

## [1] 0.5

• Vectors
• Dataframes

• Vectors: a series of things of the same type, e.g.:
• numbers: 1, 4, 9, 16, 25
• characters: “Q”, “W”, “E”, “R”, “T”, “Y”
• logicals: TRUE, FALSE, TRUE, TRUE, FALSE

• Make your own vectors with c():

name <- c("Danny", "Esther", "Karen", "Kariem")
age <- c(35, 33, 32, 41)
sex <- c("M", "F", "F", "M")
height <- c(183, 160, 155, 178)
weight <- c(85, 60, 53, 70)

name

## [1] "Danny"  "Esther" "Karen"  "Kariem"

age

## [1] 35 33 32 41

sex

## [1] "M" "F" "F" "M"

height

## [1] 183 160 155 178

weight

## [1] 85 60 53 70

• Mixing types

mixed <- c(113, "Tom", TRUE)
mixed

## [1] "113"  "Tom"  "TRUE"

name

## [1] "Danny"  "Esther" "Karen"  "Kariem"

age

## [1] 35 33 32 41

• A bit more on datatypes

• Dataframes: many vectors combined in a grid, analagous to a spreadsheet.

class_demographics <- data.frame(name, age, sex, height, weight)

class_demographics

##     name age sex height weight
## 1  Danny  35   M    183     85
## 2 Esther  33   F    160     60
## 3  Karen  32   F    155     53
## 4 Kariem  41   M    178     70

• Functions are litte machines that perform specific tasks.
• R has loads of built-in functions
• You can write your own!

ed.moveforward()

ed.moveforward(speed = "fast")

ed.moveforward(speed = "fast")
ed.turnright()
ed.turnright()
ed.moveforward(speed = "fast")

• Use R functions on your class_demographics

summary(class_demographics)

• Help files tell you how functions work.
• Clear, but technical language