# R Programming Questions and Answers – Commands – 1

This set of R Programming Language Multiple Choice Questions & Answers (MCQs) focuses on “Commands – 1”.

1. Which of the following code create n samples of size “size” with probability prob from the binomial?
a) z <- rinom(n,size,prob)
b) z <- rbinom(n,size,prob)
c) z <- binom(n,size,prob)
d) z >- nom(n,size,prob)

Explanation: To use the rbinom() function, you need to define three parameters.

2. Which of the following code create a n item vector of random normal deviates?
a) x1 <- c(snorm(n))
b) x1 <- c(pnorm(n))
c) x1 <- c(rnorm(n))
d) x1 >- c(norm(n))

Explanation: rnorm generates random deviates.

3. Which of the following statement can read csv files?

Explanation: Each row of the table appears as one line of the file.

4. Which of the following statement read a tab or space delimited file?

5. which of the following statement chose those objects meeting a logical criterion?
a) sub(dataset,logical)
b) subset(dataset,logical)
c) subsetcon(dataset,logical)
d) subcon(dataset,logical)

Explanation: R subsetting operators are powerful and fast.

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6. Which of the following statement is another way to get a subset?
a) subsetcon(dataset,logical)
b) data.df[data.df=logical]
c) sub(dataset,logical)
d) subcon(dataset,logical)

Explanation: subset(data.df,select=variables,logical) get those objects from a data frame that meet a criterion.

7. Which of the following sort a dataframe by the order of the elements in B?
a) x[rev(order(x\$B)),]
b) x[ordersort(x\$B),]
c) x[order(x\$B),]
d) x[rev(x\$B),]

Explanation: x[rev(order(x\$B)),] sort the dataframe in reverse order.

8. Which of the following is Mac menu command?
a) browse.workspace
b) browse.works
c) browser.workspace
d) a statistical transformation

Explanation: It is a Mac menu command that creates a window with information about all variables in the workspace.

9. _____ list the variables in the workspace.
a) rm(x)
b) rm(list=ls())
c) ls()
d) attach(mat)

Explanation: rm(x) removes x from the workspace.

10. ___________ remove all the variables from the workspace.
a) rm(x)
b) rm(list=ls())
c) ls()
d) attach(mat)

Explanation: attach(mat) make the names of the variables in the matrix or data frame available in the workspace.

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