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R Questions Set 44:

Quiz Mode

Low-level plotting functions that add elements to an existing plot.

High

Low

Medium

Simple

Solution:

Which of the following functions works similarly to `separate()`?

extract()

gather()

sep()

spread()

Solution:

dplyr can be integrated with the ________ package for large fast tables.

data.table

read.table

data.data

table.read

Solution:

What would be the output of the following code

> x <- 1:4 > y <- 6:9 > z <- x + y > z

7 9 11 13 14

7 9 11 13

Null

Solution:

You can check to see whether an R object is NULL using the _________ function.

is.null()

is.nullobj()

null()

as.nullobj()

Solution:

What is the output of the following R code?

`x <- 0:6 as.logical(x)`

FALSE TRUE TRUE TRUE TRUE TRUE TRUE

0 1 2 3 4 5 6

6 5 5 3 2 1

"0" "1" "2" "3" "4" "5" "6"

Solution:

which of the following is invalid?

> c(10.4, 5.6, 3.1, 6.4, 21.7) -> x

> assign("x", c(10.4, 5.6, 3.1, 6.4, 21.7))

> x <- c(10.4, 5.6, 3.1, 6.4, 21.7)

None of the above

Solution:

Pick the correct output.

`> a <- data.frame(x = rnorm(100), y = runif(100)) > b <- c(3, 4.4, 1 / 3)`

keep_image(a, b, file = “mydata.rda”)

keep(a, b, file = “mydata.rda”)

save_image(a, b, file = “mydata.rda”)

save(a, b, file = “mydata.rda”)

Solution:

Which of the following statements is used to generate a normal distribution?

dnorm(x, mean=0, sd=1, log = FALSE)

pnorm(q, mean=0, sd=1, lower.tail = TRUE, log.p = FALSE)

qnorm(p, mean=0, sd=1, lower.tail = TRUE, log.p = FALSE)

rnorm(n, mean=0, sd=1)

R Questions Set 44:

Low-level plotting functions that add elements to an existing plot.

Solution:

Which of the following functions works similarly to `separate()`?

Solution:

dplyr can be integrated with the ________ package for large fast tables.

Solution:

What would be the output of the following code

Solution:

You can check to see whether an R object is NULL using the _________ function.

Solution:

What is the output of the following R code?

`x <- 0:6 as.logical(x)`

Solution:

which of the following is invalid?

Solution:

Pick the correct output.

`> a <- data.frame(x = rnorm(100), y = runif(100)) > b <- c(3, 4.4, 1 / 3)`

Solution:

Which of the following statements is used to generate a normal distribution?

Solution:

Related Question Sets:

Related Topics:

R Questions Set 44:

Low-level plotting functions that add elements to an existing plot.

Solution:

Which of the following functions works similarly to separate()?

Solution:

dplyr can be integrated with the ________ package for large fast tables.

Solution:

What would be the output of the following code

Solution:

You can check to see whether an R object is NULL using the _________ function.

Solution:

What is the output of the following R code? x <- 0:6 as.logical(x)

Solution:

​which of the following is invalid?

Solution:

Pick the correct output. > a <- data.frame(x = rnorm(100), y = runif(100)) > b <- c(3, 4.4, 1 / 3)

Solution:

Which of the following statements is used to generate a normal distribution?

Solution:

Related Question Sets:

Related Topics:

Which of the following functions works similarly to `separate()`?

What is the output of the following R code?

`x <- 0:6 as.logical(x)`

which of the following is invalid?

Pick the correct output.

`> a <- data.frame(x = rnorm(100), y = runif(100)) > b <- c(3, 4.4, 1 / 3)`