make.power <- function(n) {
    pow <- function(x) {
        x^n
    }
    pow
}
y <- 10
f <- function(x) {
    y <- 2
    y^2 + g(x)
}
g <- function(x) {
    x * y
}
f(3)

## [1] 34

get("y", environment(g))

## [1] 10

get("y", environment(f))

## [1] 10

ls(environment(f))

## [1] "f"          "g"          "make.power" "y"

# Here, g and f are in the global env. However, y is lexically scoped in
# f.
ls()

## [1] "f"          "g"          "make.power" "y"

x <- list(a = 1:5, b = rnorm(10))
lapply(x, mean)

## $a
## [1] 3
## 
## $b
## [1] 0.146

n <- 1:4
lapply(n, rnorm)

## [[1]]
## [1] 1.486
## 
## [[2]]
## [1] -0.6582 -1.0504
## 
## [[3]]
## [1] -0.9221 -0.3621 -0.5486
## 
## [[4]]
## [1] -0.5309 -0.1827 -0.5513  2.9028

# same as lapply
sapply(n, function(x) {
    rnorm(x)
})

## [[1]]
## [1] 0.1756
## 
## [[2]]
## [1]  0.1883 -1.0643
## 
## [[3]]
## [1]  0.3771  1.2437 -1.4563
## 
## [[4]]
## [1] -0.8352 -0.6928  1.2819  0.7325

# but single elem list produces vector
sapply(n, function(x) {
    rnorm(1, x)
})

## [1] 1.020 1.233 4.120 3.324

# and constant count elem list > 1 produces matrix:
sapply(n, function(x) {
    rnorm(2, x)
})

##       [,1]   [,2]  [,3]  [,4]
## [1,] 3.074 0.5032 3.878 4.541
## [2,] 2.101 3.2964 3.977 3.755