The `apply()`

function is an alternative to writing loops, via applying a function to columns, rows, or individual values of an array or matrix.

The structure of the `apply()`

function is:
`apply(X, MARGIN, FUN, ...)`

The matrix variable used for the exercises is:
`dataset1 <- cbind(observationA = 16:8, observationB = c(20:19, 6:12))`

Answers to the exercises are available here .

Exercise 1

Using `apply()`

, find the row means of `dataset1`

Exercise 2

Using `apply()`

, find the column sums of `dataset1`

Exercise 3

Use `apply()`

to sort the columns of `dataset1`

Exercise 4

Using `apply()`

, find the product of `dataset1`

rows

Exercise 5

Required function:
`DerivativeFunction <- function(x) { log10(x) + 1 }`

Apply “`DerivativeFunction`

” on the rows of `dataset1`

Exercise 6

Re-script the formula from Exercise 5, in order to define “`DerivativeFunction`

” inside the `apply()`

function

Exercise 7

Round the output of the Exercise 6 formula to 2 places

Exercise 8

Print the columns of `dataset1`

with the `apply()`

function

Exercise 9

Find the length of the `dataset1`

columns

Exercise 10

Use `apply()`

to find the range of numbers
within the `dataset1`

columns

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