# R Programming Questions and Answers – Data Types – 3

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This set of R Programming Questions and Answers for freshers focuses on “Data Types – 3”.

1. Which of the following statement would print “0” “1” “2” “3” “4” “5” “6” for the following R code?

` > x <- 0:6`

a) as.character(x)
b) as.logical(x)
c) as.numeric(x)
d) as.num(y)

Explanation: as.character would print number from 0 to 6.

2. Point out the correct statement?
a) rep() is be used for replicating an object in various complicated ways
b) seq() function has four arguments
c) sequence() is a more general facility for generating sequences
d) numerical vectors are generated by conditions

Explanation: The simplest form is of rep representation is : > s5 >- rep(x, times=5).

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3. What will be the output of the following R code?

```x <- c("a", "b", "c")
> as.numeric(x)```

a) Warning
b) Error
c) Abnormal termination
d) Prints x

Explanation: NAs is introduced by coercion.

4. What will be the output of the following R code?

```> x <- c("a", "b", "c")
> as.logical(x)```

a) a b c
b) NA NA NA
c) 0 1 2
d) 6 8 9

Explanation: When nonsensical coercion takes place, you will usually get a warning from R.

5. Point out the correct statement?
a) The elements of a logical vector cannot have the values TRUE, FALSE, and NA
b) Matrices are vectors with a dimension attribute
c) Numerical vectors are generated by conditions
d) seq() function has four arguments

Explanation: The dimension attribute is itself an integer vector of length 2 (number of rows, number of columns).

6. Which of the following is a valid assignment?
a)

` > m <- matrix(nrow = 2, ncol = 3)`

b)

` > m <- matrix(nrow = 2, ncol = 3.5)`

c)

` > m <- mat(nrow = 2, ncol = 3)`

d)

` > m <- mat(nrow = 2, ncol = 5)`
Explanation: The valid assignment is: m lt;- matrix(nrow = 2, ncol = 3). It creates a matrix ‘m’ with 2 rows and 3 columns. The other assignments are invalid because they either have a decimal value for the number of columns (which should be a positive integer) or use an incorrect function name ‘mat’ instead of ‘matrix’.

7. What will be the output of the following R code?

``` > m <- matrix(nrow = 2, ncol = 3)
> dim(m)```

a) 3 2
b) 2 3
c) 2 2
d) 4 5

Explanation: Matrices are constructed column-wise.

8. What will be the output of the following R code?

```> m <- matrix(1:6, nrow = 2, ncol = 3)
> m```

a)

```[,1] [,2] [,3]
[1,] 1 3 5
[2,] 2 4 6```

b)

```[,0] [,1] [,2]
[1,] 1 3 5
[2,] 2 4 6```

c)

```[,1] [,2] [,3]
[1,] 1 3 6
[2,] 2 4 5```

d)

```[,5] [,6] [,7]
[1,] 1 3 6
[2,] 2 4 5```
Explanation: Matrices can also be created directly from vectors by adding a dimension attribute.

9. What will be the output of the following R code?

```> m <- 1:10
> m```

a) 1 2 3 4 5 6 7 8 9 10
b) 1 2 3 4 5 6 7 8 9 10 11
c) 0 1 2 3 4 5 6 7 8 9 10
d) 10 9 8 6 5 4 2 3 1 2

Explanation: Matrices can be created by column-binding.

10. What will be the output of the following R code?

```> x <- 1:3
> y <- 10:12
> cbind(x, y)```

a)

```x y
[1,] 6 10
[2,] 7 11
[3,] 8 12```

b)

```x y
[1,] 1 10
[2,] 2 11
[3,] 3 12```

c)

```x y
[1,] 1 4
[2,] 2 5
[3,] 3 6```

d)

```x y
[1,] 1 6
[2,] 2 5
[3,] 3 10```
Explanation: Roughly cbind() forms matrices by binding together matrices horizontally, or column-wise, and rbind() vertically, or row-wise.

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