Vectors are the fundamental one-dimensional, homogeneous containers in R; most operations are vectorized and act element-wise.

Vectors are secondary structures used only for plotting; matrices are the only fundamental objects.

Vectors are heterogeneous by default, mixing types freely without coercion.

Vectors exist only for character data; numeric data uses lists.

marks <- c(78, 85, 91, 66); mean(marks)

marks <- list(78, 85, 91, 66); sum(marks)/length(marks) produces an error

marks <- c("78", "85", "91", "66"); mean(marks) returns the same numbers

marks <- matrix(c(78,85,91,66)); mean(list(marks))

Using the combine function: x <- c(1, 2, 3)

Using assignment to a scalar: x = (1, 2, 3)

Using array literal: x := [1,2,3]

Using list constructor: x <- list(1,2,3) to make a numeric vector

c(1,2,3)

1:10

seq(0, 1, by = 0.25)

rep(TRUE, 4)

array(1:4, dim = c(2,2))

class(c(1,2,3)) returns "numeric", class(c("a","b")) returns "character", class(c(TRUE,FALSE)) returns "logical"

length(c(1,2,3)) returns "numeric", length(c("a","b")) returns "character", length(c(TRUE,FALSE)) returns "logical"

typeof(c(1,2,3)) returns "list", typeof(c("a","b")) returns "complex", typeof(c(TRUE,FALSE)) returns "integer"

class(c(1,2,3)) returns "integer" only when mixed types are present

Indexing, concatenation, arithmetic, logical comparison

Window docking, file I/O, sockets, threading

Class inheritance, polymorphism, method overriding, encapsulation

Network requests, JSON parsing, DOM manipulation, CSS styling

Operations are vectorized and apply element-wise; shorter vectors may be recycled.

Operations require explicit loops over indices for arithmetic; logical operators cannot be applied element-wise.

Arithmetic is only defined for scalars; vectors must be converted to lists first.

Logical operations work only on character vectors.

which(sales > 100)

match(100, sales)

subset(sales, 100)

sum(sales == 100)

An atomic, ordered collection of elements of the same type; valid types include numeric, character, logical, integer, and complex.

A heterogeneous container that mixes different types freely by default; valid types include table and data frame.

A two-dimensional grid; valid types include row and column.

A pointer to external objects; valid types include file and connection.

A scalar in R is simply a vector of length 1; operations treat it as a vector.

Scalars are a distinct built-in type separate from vectors.

Scalars cannot participate in arithmetic with vectors.

Vectors are only lists, while scalars are numbers.

c(6, 7, 8)

c(5, 5, 5)

c(1, 2, 3, 5)

An error because 5 is not a vector

help(), ?, example(), help.search()

open(), read(), write(), close()

install.packages(), library(), detach(), remove.packages()

ls(), rm(), get(), assign()

They provide documentation pages, usage, arguments, and examples for functions like c() and length(), making behavior clear.

They automatically rewrite code to the most efficient vectorized form.

They compile R code to machine language for faster vector operations.

They create plots by default for any vector

?c and example(length)

help.search("c()") and ?length runs examples

apropos("c") automatically executes c() on a sample

?length and example(c) are invalid

When operating on vectors of unequal length, the shorter vector’s elements are repeated in order to match the longer vector’s length.

A memory optimization that deletes unused vector elements.

A process that converts vectors into lists for reuse.

A garbage-collection technique for clearing temporary vectors.

The shorter vector is recycled; if the longer length is not a multiple of the shorter, R issues a warning.

R silently truncates the longer vector to the shorter length.

R throws an error and stops computation for any unequal lengths.

R pads with NA regardless of lengths.

c(11, 22, 13, 24) with a recycling warning

c(11, 22) only, because extra elements are ignored

c(NA, NA, NA, NA) because lengths differ

An error and no result